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
- NCT07285434Enrolling by invitationEarly Phase 1
Personalized vaccine for first-line advanced lung cancer
This study tests a personalized vaccine (Microlyvaq™) made just for your tumor, given together with standard chemo and immunotherapy (pembrolizumab). It is for people with advanced non-small cell lung cancer who have not yet started treatment for the advanced stage.
Thessaloniki, MacedoniaAges Any age - 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+ - 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+ - 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+ - NCT07157670Recruiting
Heart health study after stem cell transplant
This study looks at heart problems that can happen after a stem cell transplant from a donor (allogeneic). It aims to understand these risks better so doctors can help patients stay healthier after transplant.
ParisAges 15 years+ - NCT07129616Recruiting
Remote monitoring for childhood asthma
This study tests if remote monitoring tools can help manage asthma in children and young people. It aims to see if tracking symptoms and medication use from home improves care.
EdinburghAges 5–17 - 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+ - 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+ - NCT07110688Recruiting
Brain sensing study for mental states
This trial uses sensors and machine learning to understand mental states in healthy adults and people with epilepsy. Researchers aim to improve how we monitor and support mental health.
Downey, CaliforniaAges 18 years+ - NCT07096232Enrolling by invitation
AI vs doctor for eye surgery and keratoconus diagnosis
This study compares an AI system to a specialist eye doctor to see which is better at diagnosing vision problems like nearsightedness, farsightedness, astigmatism, and keratoconus. Your existing medical records will be used to see how well the AI performs.
Cairo, MaadiAges Any age - NCT07087171Recruiting
AI tool for patient engagement in fertility treatment
This trial tests a new AI tool designed to help patients actively participate in their own fertility care. It may benefit people starting or considering medically assisted reproduction treatments like IVF or artificial insemination.
LisbonAges 18–45 - NCT07047937Enrolling by invitation
Machine learning to predict early gastric cancer
This study uses machine learning to find patterns in patient data that might help predict early-stage stomach cancer. It could help doctors catch the disease sooner.
Wenzhou, ZhejiangAges Any age - 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 - 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+ - 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+ - NCT06277297Recruiting
Heart MRI study for Takotsubo syndrome patients
This study uses MRI to learn more about Takotsubo syndrome (a temporary heart condition often triggered by stress). If you have been diagnosed with Takotsubo and have had certain heart tests, you may be able to join.
Cagliari, ItalyAges 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 - NCT06378619Recruiting
Using a tap test and spiral drawing to diagnose tremors
This study uses a simple tapping test and drawing a spiral (like on paper) to tell the difference between tremors caused by Parkinson's disease and essential tremor. It may help you get a more accurate diagnosis without extra procedures.
Barcelona, CataloniaAges 45–79 - NCT06853301Recruiting
A faster test to find bloodstream infections
This study tests a new machine learning method to quickly identify bacteria in the blood using special sample bottles. If you are getting blood cultures done already, this may help get results faster.
GrenobleAges 18 years+ - NCT06823024Enrolling by invitation
Using speech patterns to predict treatment response in depression, PTSD, or bipolar disorder
This study tests if a computer algorithm can analyze your speech to predict how well you will respond to treatments like TMS or Spravato. It aims to create a simple tool that helps doctors choose the right treatment for you.
Sunnyvale, CaliforniaAges 18–68 - NCT04726228Recruiting
Using machine learning to improve pain assessment in advanced cancer
This trial looks at how a computer “learns” to better understand and assess cancer pain at home. It may help people with advanced cancer get more accurate pain evaluation while they are receiving pain treatment.
Naples, CampaniaAges 18 years+ - NCT05692830Recruiting
Test a wearable patch to estimate blood alcohol level
This study checks how accurately a new wearable skin patch estimates your blood alcohol level. It uses larger human testing and computer methods to improve the patch’s accuracy.
Champaign, IllinoisAges 21 years+ - NCT06682455Enrolling by invitation
Predicting AMD progression with advanced scans and AI
This study is looking at people with intermediate AMD who previously took part in the PINNACLE study. It will use advanced eye scans and machine learning to learn more about how AMD progresses and how to predict it.
ViennaAges Any age
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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.