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69 Artificial Intelligence Trials Near You
Power is an online platform that helps thousands of Artificial Intelligence patients discover FDA-reviewed trials every day. Every trial we feature meets safety and ethical standards, giving patients an easy way to discover promising new treatments in the research stage.
Learn More About PowerTailored Catheter Ablation for Atrial Fibrillation
Columbus, Ohio
This trial is testing a computer program combined with a medical procedure to help patients whose irregular heartbeat has returned. The program helps doctors find and fix the problem areas in the heart more effectively.
No Placebo Group
Trial Details
Trial Status:Active Not Recruiting
Trial Phase:Unphased
Age:21+
Key Eligibility Criteria
Disqualifiers:Obesity, Heart Failure, Pregnancy, Others
Must Be Taking:Anticoagulants
92 Participants Needed
This study will examine the impact of training primary care providers (PCPs) in motivational interviewing (MI) using artificial intelligence (AI) to augment the training process. MI is a patient-centered approach to engaging patients in their own care. There will be a control group and two intervention groups, with the intervention groups receiving a different amount of MI training. The hypothesis is that the AI-augmented MI training will result in improved patient outcomes, improved clinician wellbeing, and reduced behavioral manifestation of clinician biases. This mixed-methods project will also collect qualitative data from structured interviews and focus groups with participating PCPs to examine perceived facilitators and barriers to the use of the MI approach in primary care.
No Placebo Group
Trial Details
Trial Status:Not Yet Recruiting
Trial Phase:Unphased
Age:21+
Key Eligibility Criteria
Disqualifiers:Non-consent
150 Participants Needed
K-Talk Intervention for HPV Vaccination
Cincinnati, Ohio
The goal of this clinical trial is to test the feasibility, acceptability, and preliminary efficacy of a storytelling video-based intervention using AI chatbot technology (K-Talk) to promote HPV vaccination behavior among Korean Americans aged 18 to 45.
The main questions this study aims to answer are:
* Is the K-Talk intervention feasible for use among Korean Americans aged 18 to 45?
* Is the K-Talk intervention acceptable to the target population?
* What is the preliminary efficacy of the K-Talk intervention in promoting HPV vaccination uptake?
Participants will be Korean Americans aged 18 to 45 who are at risk for HPV infection. Participants will be asked to complete a baseline survey and then will be "randomized" into one of four groups: Group 1 (chatbot + storytelling intervention), Group 2 (chatbot only), Group 3 (storytelling only), and Group 4 will be only exposed to written didactic HPV education materials. All groups will receive written didactic HPV education materials. Researchers will compare how Group 1, a combination of AI Chatbot and storytelling intervention is more effective than other intervention groups in promoting HPV vaccination uptake among underserved, hard-to-reach Korean Americans.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Age:18 - 45
Key Eligibility Criteria
Disqualifiers:Non-Korean, Outside U.S., Age, Others
160 Participants Needed
AI Technology for Depression and Anxiety Detection
Cleveland, Ohio
Behavioral health problems, such as depression and anxiety, are common yet often are not identified by emergency department doctors and nurses. These mental health conditions can be due to medical issues or can worsen medical problems. One way investigators hope to do a better job of learning about mental health is by training Artificial Intelligence (AI) software to detect anxiety and depression by analyzing facial expression and tone of voice.
Participants are invited to participate in a study which may help improve emergency department care. An audio and video recording of the participant's responses to some simple, non-psychological questions will be analyzed by a computer to determine whether investigators can assess mood and anxiety by analyzing speech and visual patterns. The audio and video will not be listened to nor watched by study personnel, only analyzed by a computer. The investigator's hope is that it will help others in the future by aiding in the assessment of psychological state. This study is being conducted at CMC ED only.
No Placebo Group
Trial Details
Trial Status:Not Yet Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Prisoners, Critically Ill, Non-English Speakers
30 Participants Needed
Artificial Intelligence for Pulmonary Embolism
Cleveland, Ohio
Pulmonary embolism (PE) remains a high mortality and morbidity disease state. The investigators have previously shown that use of a Pulmonary Embolism Response Team (PERT) can improve overall readmission, bleeding, and mortality outcomes. Unfortunately, PERT may still be underutilized from a national standpoint and may not be readily available in underserved areas.
The use of artificial intelligence (AI) may help streamline and systematically ensure unbiased mechanism for activation of PERT for discussion of patients with siginficant clot burden and hemodynamic abnormalities. AI algorithms have been FDA approved for use of triage of the PE patient. The institutional PERT program will adapt the use of an AI algorithm for activation as routine care; the efficiency of activation will be compared to our retrospective historical comparison for efficiency and appropriateness of activation.
The active phase of the study is designed to further differentiate between patients who are considered to be intermediate-high risk category but yet do not clearly qualify for invasive therapy (catheter-directed therapy, systemic thrombolysis, or invasive hemodynamic support). These patients will undergo walking test to further understand noninvasive hemodynamic compromise and undergo 2:1 randomization to early-invasive strategy versus mtranditional medical therapy.
No Placebo Group
Trial Details
Trial Status:Not Yet Recruiting
Key Eligibility Criteria
Disqualifiers:Not Listed
390 Participants Needed
Music Therapy for Severe Dementia
Mt. Sterling, Kentucky
The goal of this pilot randomized clinical trial is to learn if a music therapy treatment, called AMUSED, can improve engagement and reduce behavioral symptoms in older adults with severe dementia who live in care facilities. The main questions it aims to answer are:
* Is it feasible to conduct a full-scale trial of AMUSED?
* Can investigators identify the best outcome measures to assess impact on behavioral symptoms of dementia?
* Does speech offer a useful indicator of treatment effectiveness? Researchers will compare a group-based music therapy treatment to a reading activity to learn if music therapy leads to greater improvements in behavioral symptoms and speech patterns.
Participants will:
* Participate in either music therapy (includes live music, singing, and rhythmic instrument playing) or a reading group with stories about life and nature and talk about memories.
* Attend small group sessions twice a week for 12 weeks, with each session lasting 40 minutes between lunch and dinner.
* Be observed and assessed for behavioral symptoms, cognition, and speech several times during treatment and at a 4-week follow-up.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Age:65+
Key Eligibility Criteria
Disqualifiers:Music Therapy Recipient, Movement Disorder, Cognitive Disability, Others
45 Participants Needed
ThinkSono System for Deep Vein Thrombosis
Pittsburgh, Pennsylvania
The purpose of this study is to confirm the safety and efficacy of the ThinkSono Guidance System, a software data collection and communication tool designed to collect ultrasound data to help detect blood clots in veins. The ThinkSono system is CE Mark approved in the European Union and in clinical use in Europe. Usually, when an ultrasound is conducted to diagnose blood clots in veins, a sonographer (trained technologist who conducts ultrasounds) and/or radiologist will conduct the procedure, including a compression ultrasound exam, and the scan may require a bulky cart and ultrasound equipment. The ThinkSono Guidance System is a mobile software application that enables other healthcare professionals such as nurses, non-radiologist physicians including general practitioners, and other allied healthcare professionals to perform the ultrasound at the point of care using guidance from the software app. This is a multi-site non-randomized, double-blinded, prospective cohort pivotal study.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Consent Not Given, Incomplete Scan, Others
500 Participants Needed
AI Diagnostic Support for Ear Infections
Pittsburgh, Pennsylvania
Ear infections are common in young children with cold symptoms, but they can be difficult to diagnose due to small ear canals, child movement, and limited viewing time. In this study, investigators will take photos of the eardrums of children 6-24 months of age with upper respiratory symptoms. The photos will be reviewed by imaging software enhanced with artificial intelligence (AI app) to determine whether the AI app changes how ear infections are diagnosed and treated. The AI app has undergone rigorous study and was found to be highly accurate; but how using this technology affects the diagnosis and treatment by clinicians has not been studied. This research may help improve diagnostic accuracy for ear infections and ensure antibiotics are prescribed only for those children who have definite ear infections.
No Placebo Group
Trial Details
Trial Status:Not Yet Recruiting
Trial Phase:Unphased
Age:6 - 24
Key Eligibility Criteria
Disqualifiers:No URI, Otorrhea, Tympanostomy Tubes
Must Not Be Taking:Antimicrobials
300 Participants Needed
AI Chatbot Education for Atrial Fibrillation
Pittsburgh, Pennsylvania
Atrial Fibrillation is a chronic disease with significant health consequences like increased risk of stroke, heart failure, heart attack and death. Educating patients about the disease is important for them to be able to understand the condition better, feel empowered and take an active part in their care plan. AI technology can potentially be used to impart such education. However, doing so with care and empathy is equally important.
Therefore, it is necessary to ensure when AI technology is used to impart education about atrial fibrillation to patients, the humane aspects of the interaction are rigorously tested. This study examines a way to impart atrial fibrillation education through interaction with an AI chatbot, that uses text and links to educational videos. To participate in this study, people need to be age 18 or older and have a history of newly diagnosed atrial fibrillation. Approximately 40 individuals will be asked to take part in this study.
The first step to the study will be reading through, understanding, and signing an informed consent. People who then agree to join the study will have a one-time interaction with the AI chatbot and structured educational material by using an iPad provided to them for the approximately 1 hour duration of the study. People in the study will obtain atrial fibrillation education by typing one by one on the iPad, up to 10 questions about the disease. Answers will include text and links to videos. Before and after atrial fibrillation education, people who join this study will be asked to fill out a survey. The study team will teach patients how to use the iPad and type in questions.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Inability To Use Device, Others
40 Participants Needed
EHR Nudges for Opioid Overdose
Pittsburgh, Pennsylvania
The goal of this cluster randomized clinical trial is to test a clinician-targeted behavioral nudge intervention in the Electronic Health Record (EHR) for patients who are identified by a machine-learning based risk prediction model as having an elevated risk for an opioid overdose.
The clinical trial will evaluate the effectiveness of providing a flag in the EHR to identify individuals at elevated risk with and without behavioral nudges/best practice alerts (BPAs) as compared to usual care by primary care clinicians.
The primary goals of the study are to improve opioid prescribing safety and reduce overdose risk.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Malignant Cancer, Hospice Care
1350 Participants Needed
Blood Test for Lung Cancer
DuBois, Pennsylvania
The PROACT LUNG study is a prospective multi-center observational study to validate a blood-based test for the early detection of lung cancer by collecting blood samples from high-risk participants who will undergo a routine, standard-of-care screening Low-Dose Computed Tomography (LDCT).
No Placebo Group
Trial Details
Trial Status:Recruiting
Age:50+
Key Eligibility Criteria
Disqualifiers:Cancer Therapy, Recent Malignancy, Transplantation, Others
Must Not Be Taking:Chemotherapy, Immunotherapy, Biologics, Others
20000 Participants Needed
AI-Assisted Colonoscopy for Polyp Detection
Chicago, Illinois
Based on prior studies, trainee and practicing gastroenterologists miss pre-cancerous polyps (adenomas and serrated polyps) during colonoscopy. The use of computer-aided detection (CADe) systems, a form of artificial intelligence (AI) has been shown to help identify colorectal lesions for practicing gastroenterologists. However, less is known how AI impacts polyp detection for trainees.
The investigators are conducting a tandem colonoscopy study wherein a portion of the colon is examined first by the trainee and then the attending physician. For each procedure, randomization will occur which will determine whether or not the trainee will utilize AI for their examination of the colon. At the end of the study, the investigators will determine whether AI helps trainees miss fewer polyps during colonoscopy. The investigators will also conduct interviews with trainees to understand how AI impacts colonoscopy training.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Polypectomy, Right Colon Surgery, Others
180 Participants Needed
AI-Enabled ECG Screening for Cardiovascular Disease
Chicago, Illinois
The goal of this clinical trial is to determine if a machine learning/artificial intelligence (AI)-based electrocardiogram (ECG) algorithm (Tempus Next software) can identify undiagnosed cardiovascular disease in patients. It will also examine the safety and effectiveness of using this AI-based tool in a clinical setting. The main questions it aims to answer are:
1. Can the AI-based ECG algorithm improve the detection of atrial fibrillation and structural heart disease?
2. How does the use of this algorithm affect clinical decision-making and patient outcomes? Researchers will compare the outcomes of healthcare providers who receive the AI-based ECG results to those who do not.
Participants (healthcare providers) will:
Be randomized into two groups: one that receives AI-based ECG results and one that does not.
In the intervention group, receive an assessment of their patient's risk of atrial fibrillation or structural heart disease with each ordered ECG.
Decide whether to perform further clinical evaluation based on the AI-generated risk assessment as part of routine clinical care.
No Placebo Group
Trial Details
Trial Status:Not Yet Recruiting
Trial Phase:Unphased
Age:40+
Key Eligibility Criteria
Disqualifiers:No AF, No PPM/ICD, Others
1000 Participants Needed
APOL1 Genetic Testing for Kidney Disease
Chicago, Illinois
Living donor (LD) kidney transplantation is the optimal treatment for patients with end-stage kidney disease (ESKD). However, LDs take on a higher risk of future ESKD themselves. African American (AA) LDs have an even greater, 3.3-fold, risk of ESKD than white LDs post-donation. Because evidence suggests that Apolipoprotein L1 (APOL1) risk variants contribute to this greater risk, transplant nephrologists are increasingly using APOL1 testing to evaluate LD candidates of African ancestry. However, nephrologists do not consistently perform genetic counseling with LD candidates about APOL1 due to a lack of knowledge and skill in counseling about APOL1. Without proper counseling, APOL1 testing will magnify LD candidates' decisional conflict about donating, jeopardizing their informed consent. Given their elevated risk of ESRD post-donation, and AAs' widely-held cultural concerns about genetic testing, it is ethically critical to protect AA LD candidates' safety through APOL1 testing in a culturally competent manner to improve informed decisions about donating.
No transplant programs have integrated APOL1 testing into LD evaluation in a culturally competent manner. Clinical "chatbots," mobile apps that use artificial intelligence to provide genetic information to patients and relieve constraints on clinicians' time, can improve informed treatment decisions and reduce decisional conflict. The chatbot "Gia," created by a medical genetics company, can be adapted to any condition. However, no chatbot on APOL1 is currently available. No counseling training programs are available for nephrologists to counsel AA LDs about APOL1 and donation in a culturally competent manner. Given the shortage of genetic counselors, increasing nephrologists' genetic literacy is critical to integrating genetic testing into practice.
The objective of this study is to culturally adapt and evaluate the effectiveness of an APOL1 testing program for AA LDs at two transplant centers serving large AA LD populations (Chicago, IL, and Washington, DC). The APOL1 testing program will evaluate the effect of the culturally competent testing, chatbot, and counseling on AA LD candidates' decisional conflict about donating, preparedness for decision-making, willingness to donate, and satisfaction with informed consent. The specific aims are to:
1. Adapt Gia and transplant counseling to APOL1 for use in routine clinical practice
2. Evaluate the effectiveness of this intervention on decisional conflict, preparedness, and willingness to donate in a pre-post design
3. Evaluate the implementation of this intervention into clinical practice by using the RE-AIM framework to longitudinally evaluate nephrologist counseling practices and LDs' satisfaction with informed consent.
The impact of this study will be the creation of a model for APOL1 testing of AA LDs, which can then be implemented nationally via implementation science approaches. APOL1 will serve as a model for integrating culturally competent genetic testing into transplant and other practices to improve patient informed consent.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Non-African Ancestry, Pregnancy, Others
390 Participants Needed
CCTA for Coronary Artery Disease
Hamilton, Ontario
Coronary artery disease (CAD) is a leading cause of death. The gold-standard test used to diagnose CAD is invasive coronary angiography (ICA). However, nearly half the patients who receive ICA are found to have no disease or non-significant disease. This means that while they receive a diagnosis, they do not receive any therapeutic benefit. This is concerning because ICA is expensive and it carries a risk to patients. A non-invasive diagnostic test, cardiac computed tomographic angiography (CCTA), has been shown to be as effective as ICA at diagnosing CAD in the right patient population, while being less expensive and less risky for patients. An optimal solution would involve screening to identify which patients are good candidates for CCTA vs. which should receive ICA. This screening tool could be used in a triage pathway to ensure that every patient gets the test that is best for them. The investigators have used Artificial Intelligence (AI) to develop a model for determining which patients should receive ICA vs. which should receive CCTA. The investigators have also developed a triage pathway to direct patients to the most appropriate test. The investigators now plan to evaluate the AI tool combined with the triage pathway through a clinical trial at Hamilton Health Sciences and Niagara Health. This model of care will reduce risk to patients, reduce wait times for ICA and reduce costs to the health care system.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Atrial Fibrillation, Severe Renal Dysfunction, Others
252 Participants Needed
AI Monitoring for Physiotherapy After Rotator Cuff Injury
Toronto, Ontario
An important part of recovery for shoulder injuries, is sticking to the exercise regimen that is prescribed by a physiotherapist. Currently, there is no proper way to measure whether patients are correcting doing their prescribed exercises at home. Researchers at Sunnybrook have tested out a Smart Physiotherapy Recognition System (SPARS), which consists of a watch that patients can wear while they are performing their physiotherapy exercises. The watch aims to learn how the exercises are done correctly when worn during supervised physiotherapy sessions, and then to record and compare whether those same exercises are being done correctly in a home setting. The main objectives of this study aims to test whether the SPARS system can effectively measure whether physiotherapy exercises are being done properly when they are done without physiotherapist supervision. Secondly, to examine whether the recovery process after shoulder injuries is improved if patients perform the physiotherapy exercises correctly.
No Placebo Group
Trial Details
Trial Status:Active Not Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Not Listed
103 Participants Needed
Adaptive Music Therapy for Well-being in Older Adults
Toronto, Ontario
This trial is testing two types of music therapy on healthy older adults aged 65+. One is regular music therapy, and the other uses technology to adjust the music to improve mood. The goal is to see if these therapies can enhance mental and emotional well-being.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Age:65+
Key Eligibility Criteria
Disqualifiers:Mental Health Diagnosis, Dementia, Others
75 Participants Needed
SPARS Rehabilitation Program for Rotator Cuff Injury
Toronto, Ontario
Physical therapy is essential for the successful rehabilitation of common shoulder injuries and following shoulder surgery. Patients may receive some training and supervision for shoulder physiotherapy through private pay or private insurance, but they are typically responsible for performing most of their physiotherapy independently at home. It is unknown how often patients perform their home exercises, if these exercises are done correctly without supervision, and how poor adherence might impact recovery.
The investigators have recently developed a Smart Physiotherapy Activity Recognition System (SPARS) for tracking home shoulder physiotherapy exercises using sensors in a commercial smart watch and artificial intelligence (AI). SPARS was successful in identifying shoulder exercises in healthy adults in the laboratory setting, and in patients undergoing physiotherapy for rotator cuff pathology. Further inquiry is required to establish the clinical effectiveness of this technology for tracking and improving patient engagement, and to investigate the potential individual impacts of its use.
No Placebo Group
Trial Details
Trial Status:Active Not Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Neurologic Deficit, Contralateral Shoulder, Failed Surgery
25 Participants Needed
Acamprosate for Alcoholism
Bethesda, Maryland
Background:
Chronic heavy drinking can cause alcohol use disorder (AUD). AUD changes how the brain works. People with AUD may drink compulsively or feel like they cannot control their alcohol use. Acamprosate is an FDA-approved drug that reduces anxiety and craving in some, but not all, people with AUD.
Objective:
To learn more about how acamprosate affects brain function in people with AUD.
Eligibility:
People aged 21 to 65 years with moderate to severe AUD.
Design:
Participants will stay in the clinic for 21 days after a detoxification period of approximately 7 days.
Acamprosate is a capsule taken by mouth. Half of participants will take this drug 3 times a day with meals. The other half will take a placebo. The placebo looks like the study drug but does not contain any medicine. Participants will not know which capsules they are taking.
Participants will have a procedure called electroencephalography (EEG): A gel will be applied to certain locations on their scalp, and a snug cap will be placed on their head. The cap has sensors with wires. The sensors detect electrical activity in the brain. Participants will lie still and perform 2 tasks: they will look at different shapes and press a button when they see a specific one; and they will listen to tones and press dedicated buttons when they hear the corresponding tones.
Participants will have 2 EEGs: 1 on day 2 and 1 on day 23 of their study participation. They may opt to have up to 4 more EEG studies (one on day 13 and one on each of the three follow-up visits) and 2 sleep studies, in which they would have sensors attached to their scalp while they sleep.
Participants may have up to three follow-up visits for 6 months.
Trial Details
Trial Status:Recruiting
Trial Phase:Phase 4
Age:21 - 65
Key Eligibility Criteria
Disqualifiers:Pregnancy, Head Trauma, Epilepsy, Others
Must Not Be Taking:Naltrexone, Disulfiram, Benzodiazepines, Others
48 Participants Needed
Sound-based Treatment for Tinnitus
Toronto, Ontario
The goal of this clinical trial is to assess the effectiveness of a sound-based passive treatment for reducing stress and annoyance induced by tinnitus, and how this therapy may improve tinnitus sufferers' quality of life. The main questions it aims to answer are: • \[question 1: to assess the efficacy of the LUCID/VIBE in managing the tinnitus handicap (measured by the reducing of the annoyance/stress response to tinnitus) contributing to the improvement of the quality of life of people living with tinnitus\] and • \[question 2: assess the efficacy of LUCID/VIBE in providing temporary relief through masking, such that it results in a reduction of the perceived loudness of tinnitus\]. Participants will \[use the VIBE app for 24 minutes a day for a period of 4 weeks. There will be two conditions, a Noise condition (the control condition in which the investigator will administer white noise) and the VIBE condition (the treatment condition). One approach involves broad-band masking with noise (Noise Condition), while the other uses music (LUCID Condition). Implementation of the noise condition will mirror the LUCID condition in terms of ease of access, look, feel, so that one condition does not look less professional than the other. Both conditions will be administered through the same app, and only the sound conditions will differ (white noise vs. LUCID music). All participants will be exposed to both the treatment and control conditions with the order of conditions counter-balanced (i.e., a cross-over design).
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Age:50 - 79
Key Eligibility Criteria
Disqualifiers:Age, Pulsatile Tinnitus, Other Treatments, Others
50 Participants Needed
Why Other Patients Applied
"I have dealt with voice and vocal fold issues related to paralysis for over 12 years. This problem has negatively impacted virtually every facet of my life. I am an otherwise healthy 48 year old married father of 3 living. My youngest daughter is 12 and has never heard my real voice. I am now having breathing issues related to the paralysis as well as trouble swallowing some liquids. In my research I have seen some recent trials focused on helping people like me."
AG
Paralysis PatientAge: 50
"I've been struggling with ADHD and anxiety since I was 9 years old. I'm currently 30. I really don't like how numb the medications make me feel. And especially now, that I've lost my grandma and my aunt 8 days apart, my anxiety has been even worse. So I'm trying to find something new."
FF
ADHD PatientAge: 31
"I was diagnosed with stage 4 pancreatic cancer three months ago, metastatic to my liver, and I have been receiving and responding well to chemotherapy. My blood work revealed that my tumor markers have gone from 2600 in the beginning to 173 as of now, even with the delay in treatment, they are not going up. CT Scans reveal they have been shrinking as well. However, chemo is seriously deteriorating my body. I have 4 more treatments to go in this 12 treatment cycle. I am just interested in learning about my other options, if any are available to me."
ID
Pancreatic Cancer PatientAge: 40
"My orthopedist recommended a half replacement of my right knee. I have had both hips replaced. Currently have arthritis in knee, shoulder, and thumb. I want to avoid surgery, and I'm open-minded about trying a trial before using surgery as a last resort."
HZ
Arthritis PatientAge: 78
"As a healthy volunteer, I like to participate in as many trials as I'm able to. It's a good way to help research and earn money."
IZ
Healthy Volunteer PatientAge: 38
Robot Therapy for Anxiety
Toronto, Ontario
Children experience pain and distress in clinical settings every day. The negative consequences of unaddressed pain can be both short-term (e.g. fear, distress, inability to perform procedures) and long-term (e.g. needle phobia, anxiety).
In previous small studies, a humanoid robot has been used to deliver cognitive-behavioural therapy during needle procedures. The results of these early studies have been positive, showing high acceptance among children as well as promising initial clinical results. However, these studies all had critical technical limitations: the robot was remotely operated and used purely scripted behaviour with limited Artificial Intelligence support. This reduced the potential to offer personalized support to children. In this project, the study team aims to address this limitation by developing and evaluating a clinically relevant and responsive artificial intelligence-enhanced social robot.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Age:5 - 11
Key Eligibility Criteria
Disqualifiers:Medically Unstable, Unconscious, Neurocognitive Delays, Others
90 Participants Needed
Rosie Chatbot Assistance for Pregnancy and Infant Care
College Park, Maryland
Rosie the Chatbot is an educational chatbot that moms can have on their computers or cellphones and will work by moms typing in their questions about pregnancy, health, infant milestones, and other variety of health related topics and receiving back a response immediately. Rosie only provides information from verified sources such as children's hospitals, health organizations and government agencies. Rosie does not ask moms to provide any personal information on her or her child, her chat is completely confidential, it works in English and Spanish and will be free.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Age:14 - 99
Sex:Female
Key Eligibility Criteria
Disqualifiers:Non-hispanic White, Others
400 Participants Needed
SEPSys and RESCUE Scores for Sepsis Prediction
Largo, Maryland
This study is designed to test two new risk scores - one designed to predict a patient's four-hour risk of developing sepsis and one designed to predict a patient's four-hour risk of deterioration (cardiac arrest, death, unplanned ICU transfer, or rapid response team call). The goal of this study is to improve provider awareness of a patient's risk of these two negative outcomes by providing them with new risk scores. The primary outcome will be the time from when the risk score becomes elevated to when vital signs such as heart rate or blood pressure are measured, suggesting an increased awareness.
No Placebo Group
Trial Details
Trial Status:Not Yet Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Pediatric, Psychiatric, Sepsis, High RESCUE, Others
150000 Participants Needed
AI Assistance for Cognitive Overload
Chapel Hill, North Carolina
The goal of this study is to explore cognitive burden perceptions among physicians in relation to case report writing. Furthermore, this study evaluates the use of artificial intelligence (AI) assistance as a tool to reduce cognitive burden among providers preparing and submitting case reports. If an AI-tool is helpful in this setting, it may potentially help increase reporting of rare medical events and thereby improve the evidence base for care of these patient populations. This study will occur at a single time point which is expected to last approximately 2 hours. This session will include reviewing two rare tumor cases and then writing a clinical vignette with and without AI assistance.
No Placebo Group
Trial Details
Trial Status:Not Yet Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Non-physicians, Non-medical Students, Others
10 Participants Needed
AI Support for Mental Health Conditions
Alton, Illinois
The goal of this clinical trial is to assess the effectiveness of an artificial intelligence (AI) platform for case managers in a nonprofit health system specializing in mental health and substance use disorder. The main questions it aims to answer are:
1. Is the AI platform acceptable and feasible for case managers?
2. Does the AI platform improve providers' productivity and reported interventions? Participants will be approximately 30 case managers and their 250 adult clients receiving case management services. Researchers will compare the provider productivity and work satisfaction prior to the implementation of the AI platform to following its implementation.
No Placebo Group
Trial Details
Trial Status:Enrolling By Invitation
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Concurrent Research Study, Others
280 Participants Needed
Machine Learning Monitoring for Clinical Deterioration
Madison, Wisconsin
In this study, the investigators will deploy a software-based clinical decision support tool (eCARTv5) into the electronic health record (EHR) workflow of multiple hospital wards. eCART's algorithm is designed to analyze real-time EHR data, such as vitals and laboratory results, to identify which patients are at increased risk for clinical deterioration. The algorithm specifically predicts imminent death or the need for intensive care unit (ICU) transfer. Within the eCART interface, clinical teams are then directed toward standardized guidance to determine next steps in care for elevated-risk patients.
The investigators hypothesize that implementing such a tool will be associated with a decrease in ventilator utilization, length of stay, and mortality for high-risk hospitalized adults.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Under 18, Not In ECART Unit
30000 Participants Needed
Ambient AI for Burnout
Madison, Wisconsin
The goal of this clinical trial is to learn whether using Ambient Artificial Intelligence for provider documentation will enhance provider well-being and improve documentation quality.
Participants will complete their documentation using the Ambient AI software.
No Placebo Group
Trial Details
Trial Status:Active Not Recruiting
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Planned Leave, No Apple Device, Not On Haiku, Virtual Scribe
66 Participants Needed
AI Screening for Vision Loss from Diabetes
Madison, Wisconsin
This study aims to investigate whether a novel artificial intelligence based screening strategy (AI-Based point of caRe, Incorporating Diagnosis, SchedulinG, and Education or AI-BRIDGE), which allows primary care providers to screen patients for vision-threatening diabetic eye disease in the primary care clinic, improves screening and follow-up care rates across race/ethnicity groups and reduces racial/ethnic disparities in screening.
No Placebo Group
Trial Details
Trial Status:Recruiting
Trial Phase:Unphased
Age:22+
Key Eligibility Criteria
Disqualifiers:Diabetic Eye Disease, Others
4000 Participants Needed
Pediatric eCART for High-Risk Outcomes
Madison, Wisconsin
This is a study comparing 3 years of retrospective data (pre-implementation) to 2 years of prospective data after the implementation of a pediatric version of Electronic Cardiac Arrest Risk Triage (pediatric eCART), a clinical decision support (CDS) tool that uses electronic health records (EHR) to identify patients with high risk for life threatening outcomes. Up to 30,000 encounters with pediatric patients will be assessed. Acceptability of the pediatric eCART intervention will also be measured from pediatric nurse clinicians.
No Placebo Group
Trial Details
Trial Status:Not Yet Recruiting
Trial Phase:Unphased
Age:< 17
Key Eligibility Criteria
Disqualifiers:Neonates, Birth Encounters, Others
30000 Participants Needed
AI Wellness Chatbot for Depression and Anxiety
Philadelphia, Pennsylvania
This study is testing the acceptability and efficacy of an AI enabled mental health chatbot (Elomia) as a resource of college student wellness.
No Placebo Group
Trial Details
Trial Status:Enrolling By Invitation
Trial Phase:Unphased
Key Eligibility Criteria
Disqualifiers:Severe Depression, Suicidality
60 Participants Needed
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Frequently Asked Questions
How much do Artificial Intelligence clinical trials pay?
Each trial will compensate patients a different amount, but $50-100 for each visit is a fairly common range for Phase 2–4 trials (Phase 1 trials often pay substantially more). Further, most trials will cover the costs of a travel to-and-from the clinic.
How do Artificial Intelligence clinical trials work?
After a researcher reviews your profile, they may choose to invite you in to a screening appointment, where they'll determine if you meet 100% of the eligibility requirements. If you do, you'll be sorted into one of the treatment groups, and receive your study drug. For some trials, there is a chance you'll receive a placebo. Across Artificial Intelligence trials 30% of clinical trials have a placebo. Typically, you'll be required to check-in with the clinic every month or so. The average trial length for Artificial Intelligence is 12 months.
How do I participate in a study as a "healthy volunteer"?
Not all studies recruit healthy volunteers: usually, Phase 1 studies do. Participating as a healthy volunteer means you will go to a research facility several times over a few days or weeks to receive a dose of either the test treatment or a "placebo," which is a harmless substance that helps researchers compare results. You will have routine tests during these visits, and you'll be compensated for your time and travel, with the number of appointments and details varying by study.
What does the "phase" of a clinical trial mean?
The phase of a trial reveals what stage the drug is in to get approval for a specific condition. Phase 1 trials are the trials to collect safety data in humans. Phase 2 trials are those where the drug has some data showing safety in humans, but where further human data is needed on drug effectiveness. Phase 3 trials are in the final step before approval. The drug already has data showing both safety and effectiveness. As a general rule, Phase 3 trials are more promising than Phase 2, and Phase 2 trials are more promising than phase 1.
Do I need to be insured to participate in a Artificial Intelligence medical study?
Clinical trials are almost always free to participants, and so do not require insurance. The only exception here are trials focused on cancer, because only a small part of the typical treatment plan is actually experimental. For these cancer trials, participants typically need insurance to cover all the non-experimental components.
What are the newest Artificial Intelligence clinical trials?
Most recently, we added Arterial Measurement Sites for Hemodynamic Management, AI Tool for Breast Cancer Screening and AI Screening for Vision Loss from Diabetes to the Power online platform.
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