Clinical trials
Machine Learning clinical trials
Below are recruiting machine learning clinical trials, each written for real people, not researchers. We’re tracking 90 recruiting studies, each written for real people, not researchers, below.
Recruiting studies
- NCT06380049Recruiting
Predicting fall risk after stroke with sensors and AI
This study uses special sensors and machine learning to predict fall risk in people who recently had a stroke. It aims to help you and your care team take steps to prevent falls.
Seoul, JongnoAges 19 years+ - NCT06531317Recruiting
EEG and brain stimulation for nerve pain after spinal cord injury
This study tests whether a personalized brain stimulation treatment (using a non-invasive technique called tDCS) can help reduce nerve pain in people with spinal cord injury. The researchers will also use EEG (a cap that records brain activity) to see how your brain responds.
Badalona, BarcelonaAges 18–99 - NCT07690813Recruiting
AI model to predict nearsightedness with a non-dilated eye exam
This study uses an AI model to predict your nearsightedness prescription using a quick, non-dilated eye exam instead of the usual dilated exam. If you are between 18 and 60, have nearsightedness, and no major eye surgeries or conditions, you may be a good fit.
JiangxiAges 18–47 - 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+ - NCT06806163Recruiting
Preventing Opioid Overdoses with Smart Reminders
This study tests whether a computer program can help doctors and patients have a conversation about safe opioid use. It uses information from your medical records to send reminders to your doctor, aiming to prevent overdoses.
Pittsburgh, PennsylvaniaAges 18 years+ - 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+ - 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+ - NCT06899490Recruiting
Acupuncture study for anxiety with tongue analysis
This trial uses machine learning to analyze tongue color and anxiety scores in people getting acupuncture for anxiety. It aims to see if tongue color can help predict treatment response.
NarbonneAges 18 years+ - NCT06902688Recruiting
Pharmacogenetic testing for kids at SickKids
This trial offers pharmacogenetic testing to children admitted to The Hospital for Sick Children to help doctors choose safer, more effective medications based on their genes.
Toronto, OntarioAges 6 months–18 years - NCT06934343Recruiting
Personalized therapy for advanced lung cancer using data
This trial uses real-world data to study how to personalize treatment for advanced non-small cell lung cancer. It looks at medical records from 2011 to 2024 to find the best therapy approaches.
Salt Lake City, UtahAges Any age - NCT07010380Recruiting
Finding parathyroid glands with AI imaging during thyroid surgery
This trial uses a special camera and AI software during thyroid or parathyroid surgery to help surgeons identify and protect the parathyroid glands. The goal is to reduce complications like low calcium levels after surgery.
Fuzhou, FJAges 18 years+ - NCT07030166Recruiting
Predicting kidney injury risk after non-cardiac surgery
This trial uses machine learning to predict the risk of acute kidney injury (AKI) after non-cardiac surgery. If you are 18 or older and having this type of surgery, it may help understand your risk and guide care.
NanjingAges 18 years+ - NCT07030998Recruiting
Using smartwatch data to find early signs of infection in kids with cancer
This trial uses an Apple Watch and a smartphone app to track health data and detect early signs of infection in children and teens getting cancer treatment. The goal is to catch problems early so they can be treated quickly.
Parkville, VictoriaAges 5–18 - NCT07108660Recruiting
Predicting and reducing bloodstream infections from central lines
This trial uses machine learning to predict infections that can happen with central lines (special IVs placed in large veins) and aims to reduce how often they occur. It focuses on hospitals with the highest infection rates, so you might be eligible if you receive care at one of these hospitals.
Anchorage, AlaskaAges 18 years+ - NCT07126106Recruiting
Testing a computer program to find sepsis earlier in the ICU
This study tests a new computer program that helps doctors find serious infections (sepsis and bacteremia) earlier in ICU patients. If you join, the program will analyze your health data to see if it can better predict these infections, which could help you get faster treatment.
Seyrantepe, IstanbulAges 18 years+ - NCT07227233RecruitingPhase 2
AI-guided retrial of CDK4/6 inhibitors for advanced breast cancer
This trial tests whether an artificial intelligence (AI) tool can help doctors decide if it is safe and effective to give you a second course of a CDK4/6 inhibitor drug (like palbociclib, ribociclib, or abemaciclib) plus hormone therapy for advanced (unresectable or metastatic) HR+/HER2- breast cancer. The goal is to only treat people whose cancer is likely to respond based on a special AI analysis of their tumor tissue.
La Jolla, CaliforniaAges 18 years+ - NCT07275190Recruiting
Machine learning to tell apart two rare diseases
This trial uses computer models (machine learning) to help doctors better distinguish between two rare conditions that both cause high levels of a certain white blood cell (eosinophil). The goal is to make diagnosis faster and more accurate, which could lead to more targeted treatment.
PaviaAges 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 - 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 - 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+ - 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+ - 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 - 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.
Istanbul, EyupsultanAges 10–18
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Common questions
- Are there clinical trials for machine learning?
- Yes. Clin2 currently lists 90 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.