Clinical trials
Machine Learning clinical trials
Below are recruiting machine learning clinical trials, each written for real people, not researchers. We’re tracking 93 recruiting studies, each written for real people, not researchers, below.
Recruiting studies
- NCT07620119Recruiting
AI-assisted heart attack diagnosis in patients with LBBB
This study tests whether artificial intelligence can help doctors more accurately diagnose heart attacks in patients who have a specific heart rhythm pattern called Left Bundle Branch Block (LBBB). The goal is to improve emergency care by reducing delays in identifying who needs urgent treatment.
Konya, KaratayAges 18 years+ - NCT07618416Recruiting
Blood Pressure Prediction Before Anesthesia in Older Adults
This study tests a computer model that uses heart-rhythm measurements to predict whether your blood pressure will drop dangerously after anesthesia begins. If accurate, it could help doctors prepare and protect you during surgery.
Beijing, ChinaAges 65 years+ - NCT07611838Recruiting
Predicting ABPA Recurrence Using Blood and Immune Markers
This study helps doctors predict whether allergic bronchopulmonary aspergillosis (ABPA)—a serious lung condition caused by fungal allergy—will come back after treatment. Researchers will analyze blood samples and immune system markers to identify patients at higher risk of relapse, which could improve how doctors monitor and treat you.
Jinan, ShandongAges 18–80 - NCT07558785Enrolling by invitation
Testing speech and memory checks at home for early thinking problems
This study uses a video-based system at home to check your speech and memory, helping doctors spot thinking problems early using artificial intelligence. The goal is to see if this simple, at-home test can reliably catch early memory and thinking changes.
PilsenAges 40 years+ - NCT07556042Recruiting
Machine Learning to Predict Scoliosis Progression in Teens
This study uses artificial intelligence to predict how adolescent scoliosis (curvature of the spine) might progress over time. By understanding which teens are most at risk, doctors hope to catch and treat the condition earlier.
IstanbulAges 10–18 - NCT07542509Recruiting
Digital sound analysis for newborn heart screening
This study uses digital technology to analyze heart sounds in newborns under 30 days old. The goal is to develop a simple, non-invasive way to detect heart problems early using sound recordings.
Bologna, BOAges 1 week–4 weeks - NCT07521111Recruiting
Stomach Blood Flow and Feeding Tolerance in Critical Illness
This study examines whether measuring blood flow in the stomach using ultrasound can predict which hospitalized patients will struggle to tolerate tube feeding. Researchers hope this simple test might help doctors adjust feeding plans earlier and improve patient outcomes.
ShanghaiAges 18 years+ - NCT06767254Recruiting
Using AI to predict early return of multiple myeloma
This study uses artificial intelligence to analyze how multiple myeloma may lead to early relapse. It may help doctors better predict and manage the disease.
Meldola, Forlì-CesenaAges 18 years+ - NCT06773598Recruiting
MRI-based machine learning tool for prostate cancer
This trial tests a computer model that learns from MRI scans to predict prostate cancer. If you have had a prostate MRI showing suspicious areas and are scheduled for a biopsy, joining may help improve how cancer is detected.
BolognaAges 18 years+ - NCT07488585Recruiting
New ultrasound probe for thyroid imaging
This trial tests a new ultrasound probe designed to take better images of thyroid nodules. It may help improve the monitoring of nodules over time.
Dartmouth, Nova ScotiaAges 18 years+ - NCT07463833Recruiting
AI review of prostate cancer radiation plans
This study tests if an AI tool can improve the safety review of radiation treatment plans for prostate cancer. Patients continue their normal treatment while the AI helps doctors check the plans.
Chapel Hill, North CarolinaAges 18 years+ - NCT05176769Recruiting
AI system to review hospital heart records in Greece
This trial uses a computer program to automatically study heart-care information stored in hospital computer records. It may help hospitals find insights faster from routine medical documentation.
AlexandroupoliAges 18 years+ - NCT07450612Recruiting
Blood test and AI for early colorectal cancer detection
This study uses a simple blood test (liquid biopsy) and computer analysis to find early signs of colorectal cancer, precancerous growths, and Lynch syndrome. It aims to improve early detection and monitor for any remaining cancer after treatment.
Milan, LombardyAges 18 years+ - NCT07449182Recruiting
AI Educational Agent for Medical Machine Learning
This trial tests an AI educational agent that helps teach medical machine learning. If you are a medical graduate student in the Greater Bay Area who has already taken a machine learning course and completed certain prerequisites, you may be able to join.
Guangzhou, GuangdongAges Any age - NCT07447596Recruiting
Lung health study using breathing tests and AI
This study uses a simple breathing test called oscillometry along with machine learning to better understand lung conditions like COPD, asthma, and interstitial lung disease. It may help find new ways to diagnose and track these diseases.
BarcelonaAges 18–99 - NCT07451509Recruiting
Machine learning foot pressure study in healthy adults
This trial studies how machine learning can analyze foot pressure during standing or walking. It aims to improve understanding of foot mechanics in healthy adults.
Olomouc, CzechiaAges 18 years+ - NCT07428694Recruiting
Detecting air leaks during breathing support
This trial tests a machine learning tool to detect if air is leaking while using a breathing machine at night. It may help people who use a non-invasive ventilator at home get better care.
OsloAges 18 years+ - NCT07418632Recruiting
Motion training for neck pain using smart classification
This study tests a special motion-training program for people with neck pain. It uses a computer to classify and guide your movements, which may help reduce pain better than usual care.
LjubljanaAges 18–65 - NCT06819618Recruiting
Predicting heart failure outcomes with machine learning
This trial uses machine learning to analyze data from a smartwatch to predict how heart failure progresses. It may help doctors better understand your condition and tailor treatments.
Goettigen, Lower SaxonyAges 18 years+ - NCT07405398Recruiting
Smartwatch study to detect opioid use and withdrawal
This study uses a smartwatch to track wrist data and help detect when someone is using opioids or experiencing withdrawal. It's designed for people with opioid use disorder who are starting or already on treatment with methadone or buprenorphine.
Wilmington, North CarolinaAges 22 years+ - NCT05771844Recruiting
Home sleep treatment for older adults with memory changes
This study tests whether a home sleep therapy program can improve symptoms in older adults who have amnestic mild cognitive impairment (MCI) or help compare to people without MCI. It may be useful if your main issue is memory or thinking changes and you also have sleep problems.
Winston-Salem, North CarolinaAges 40–85 - NCT06841653Recruiting
AI model to predict risk and improve treatment for endometrial cancer
This trial is testing whether a computer model powered by artificial intelligence can better predict outcomes for people with endometrial cancer or related conditions. It uses patient data and tissue samples to see if the model can help doctors choose the best care.
RomeAges 18 years+ - NCT07325513Recruiting
Brain stimulation for Gulf War-related pain
This study tests whether a type of brain stimulation (repeated transcranial magnetic stimulation, or rTMS) can help reduce headaches and body pain in veterans with Gulf War Illness. If you are a Gulf War veteran with ongoing moderate-to-severe pain, this trial could help find a new way to manage your symptoms.
San Diego, CaliforniaAges 18–65 - NCT05876598Recruiting
Predict bloodstream infection risk using a computer model
This study builds and tests a computer (machine-learning) model to predict bloodstream infections based on what happens in the first days of care. It may help doctors start the right antibiotic faster for patients who truly have an infection.
RomeAges 18 years+
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Common questions
- Are there clinical trials for machine learning?
- Yes. Clin2 currently lists 93 recruiting machine learning studies from the U.S. registry, each rewritten for real people, not researchers, so you can see what it’s testing and who it’s for.
- How do I know if I qualify for a machine learning trial?
- Each study lists its eligibility criteria — rules about age, diagnosis, and prior treatments. On every Clin2 trial page we explain these in words written for real people and offer a short, optional pre-screen for a fit read. The study team makes the final decision.
- Does it cost anything to join a machine learning trial?
- Using Clin2 is always free. Many trials cover the cost of the study treatment and related visits; some reimburse travel. The study team explains exactly what’s covered before you decide.
Related conditions
Clin2 helps you find and understand clinical trials and does not provide medical advice. Study data comes from ClinicalTrials.gov. Talk with your doctor about whether a specific trial is right for you.