Condition
Artificial Intelligence (AI) clinical trials and research
As of November 12, 2026, Find a Trial lists 43 Artificial Intelligence (AI) clinical trials that are recruiting, at sites in 19 countries (most in China (13), Taiwan (5), Italy (5)). 1 was first registered in the last 30 days. By phase: Phase 4 (1). There are also 10 NIH-funded research projects on Artificial Intelligence (AI), with $3.5 million in listed awards. Every study is explained in plain English. Data from ClinicalTrials.gov and NIH RePORTER, updated November 12, 2026.
- 43Clinical trials
- 10NIH research projects
- 1New in 30 days
- 19Countries
Newest Artificial Intelligence (AI) clinical trials
All recruiting trials (43)
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AI-assisted whole-course management for safe medicine use in advanced solid tumors
A real-world study compares a smartphone-based digital management system with usual care to see if it reduces drug-related problems and healthcare needs for adults with advanced solid tumors receiving cancer therapy.
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AI-assisted and traditional workflows for admission diagnosis and management planning
This trial tests whether an AI-agent workflow helps doctors make better admission diagnoses and care plans on simulated cases, compared with plain AI-assisted and traditional workflows.
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Prediction score for death or lung transplant in emphysema caused by alpha-1 antitrypsin deficiency
This study tests a new prediction tool to identify people with emphysema due to alpha-1-antitrypsin deficiency who are at high risk of death or needing a lung transplant.
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Timing of AI Help in Chest X-Rays: Does When AI Becomes Visible Change How Clinicians Read Images?
Doctors test chest X-ray interpretation with AI information shown either before or after they start reviewing the image to see how timing affects their search patterns and decisions.
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Does AI-based cephalometric tracing match digital manual tracing for orthodontic measurements?
This study tests whether AI-powered cephalometric analysis can produce measurements similar to traditional digital tracing in 100 patient radiographs.
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Heart score calculator test using GPT-4o and Claude in chest pain patients
This study tests whether two large language models can calculate HEART scores from patient notes and predict 30-day adverse heart events in adults with chest pain in the emergency department.
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AI-simplified versus original patient education materials for parents of children with osteogenesis imperfecta
This tests whether AI-simplified educational materials help parents of children with osteogenesis imperfecta understand the condition better than the original materials.
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Behavioral parent training with optional AI support for children with disruptive behaviors
This trial will test whether adding a 24/7 AI assistant to online group behavioral parent training helps parents manage children aged 5–12 with disruptive behaviors.
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Predicting early mobility after hip or knee replacement using a machine learning model
A machine learning model is being tested to see if it can predict which patients will walk sooner after hip or knee replacement surgery.
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Building a short video and audio database of cancer pain to help AI recognize patient pain
This project collects short face and voice recordings from adults with cancer who do and don't have pain to help test AI that tries to recognize pain from expressions.
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AI-assisted analgesia copilot to guide remifentanil dosing during general anesthesia
This project will test an AI 'co-pilot' that monitors multiple physiological signals during general anesthesia to guide remifentanil dosing and reduce over- or under-dosing for adults having elective surgeries of 2–4 hours.
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Making AI triage more accurate for patients contacting their GP
This project will test whether updated AI in the Patchs online consultation system can make triage decisions more accurate and fair for patients contacting GP practices in England.
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Home-based mobile neurological check for people with brain tumors
This project will test whether people with brain tumors older than 5 can use the Iskhaa Android app to do guided self-neurological exams, upload short videos, and have an AI model detect changes that might predict neurological worsening.
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AI-ECG strategy to identify people who may need implanted heart devices
This trial will test whether using an artificial intelligence-enhanced ECG to alert doctors helps find patients who need pacemakers or other implanted heart devices sooner than usual care.
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Computer-vision detection of delirium from ICU patients' facial expressions
This project tests whether a smartphone app using computer vision can detect delirium from facial expressions in adult neurocritical care patients.
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Multi-center artificial intelligence-based quantitative echocardiography evaluation
This project will test whether AI can automatically and accurately measure heart chamber sizes, volumes, and function from echocardiograms in adults with common cardiovascular conditions.
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Using AI analysis of eye images to identify Traditional Chinese Medicine constitutions
This project will test whether an AI model can use eye images to identify biased TCM constitutions in adults aged 18–60 with chronic diseases.
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AI prediction of lymph node spread in high‑risk prostate cancer
This study will test an AI model that uses MRI, pathology images, and routine clinical data to see if high‑risk prostate cancer patients have lymph node spread before prostate removal.
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AI-driven support to improve patient engagement during IVF
This project will test whether an AI tool that provides personalized live-birth probabilities and tailored messages helps people aged 18–45 undergoing IVF/ICSI or donor cycles stay engaged with treatment and follow clinic recommendations.
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Deep-learning ECG to detect pulmonary hypertension
This trial tests whether an AI-powered ECG can spot high blood pressure in the lungs (pulmonary hypertension) in adults aged 50–85 who have had a recent ECG.
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Single radiologist with AI support versus two radiologists for screening mammograms
This trial will see if one radiologist aided by AI can match the performance of the usual two-radiologist reading for screening mammograms in women aged 45–69.
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AI-assisted diagnosis of colorectal tubular adenomas using white-light, magnifying chromoendoscopy (including NBI) and pathology images
This project will test whether an AI tool that combines white-light, magnified chromoendoscopy, NBI, and pathology images can help doctors identify colorectal tubular adenomas in adults undergoing colonoscopy.
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Using cardiac MRI and AI to predict outcomes after STEMI
This project will try to use routine cardiac MRI scans plus AI to see if imaging features can predict long-term outcomes in people who had a STEMI treated with primary PCI.
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AI pharmacy chatbot for adults with high blood sugar, blood pressure, or cholesterol in Hong Kong
We will test a WhatsApp AI pharmacy chatbot that answers Hospital Authority–prescribed medication questions for adults in Hong Kong with hyperglycaemia, hypertension, or hyperlipidaemia and their caregivers.
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Comparing AI and human interpretation for lung cancer screening
This study tests whether an AI system can read CT scans for lung cancer as well as human doctors do in community health centers.
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AI-powered nursing care robot to assist healthcare workers
This study is testing a new AI-powered robot to see if it can help nurses do their jobs better and make patient care more efficient.
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AI-guided app to help manage type 2 diabetes
This project will try an AI-guided app that uses glucose and activity data to give adults with type 2 diabetes personalized medication, diet, and exercise suggestions to help lower blood sugar.
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Real-time AI system to measure colorectal polyp size during colonoscopy
This will test a real-time AI tool called EndoAIM that automatically measures polyp diameter during colonoscopies in adults having screening, surveillance, or symptom evaluation.
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PEAR: an AI chatbot to explain anaesthesia risks and consent.
This trial will test whether PEAR, a multilingual AI chatbot, helps adults having elective surgery understand anaesthesia risks, feel more satisfied, and have less preoperative anxiety compared with the usual face-to-face consent conversation.
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Screening mammograms with or without AI assistance for breast cancer detection
This trial will try using an FDA-cleared AI tool to help radiologists read screening mammograms for adults to see if it finds more cancers and reduces unnecessary callbacks.
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AI-assisted ECG to speed diagnosis and treatment of occlusion heart attacks under a pay-for-performance program
This project will test whether adding an AI tool that flags ECGs for occlusion heart attacks and linking those alerts to a pay-for-performance program helps emergency department patients who get ECGs get diagnosed and treated faster and with better outcomes.
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AI-ECG alerts to catch early atrial fibrillation risk
This trial tests whether an AI-powered ECG alert can help doctors find people at high risk of developing atrial fibrillation so they can be given continuous heart-rhythm monitoring.
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Creating a video library of endoscopy procedures to improve AI quality reporting and education
This study is creating a video library of endoscopy procedures to help improve the quality of care for patients with rectal cancer or inflammatory bowel disease and to train future doctors.
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Predicting heart function using echocardiography and body composition data
This study is testing if combining heart ultrasound results with body composition data can help predict heart function in people with and without heart failure.
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AI-supported education for patients undergoing mastectomy
This study is testing whether an AI-supported education program can help reduce fear and anxiety in women getting a mastectomy for breast cancer compared to standard education.
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Using artificial intelligence to improve colonoscopy detection rates
This study is testing whether using artificial intelligence during colonoscopies can help doctors find more polyps and early signs of colorectal cancer in patients.
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Using AI to improve detection and prediction of cerebral aneurysms
This study is testing whether using artificial intelligence can help doctors find and predict the risk of unruptured brain aneurysms more accurately to better protect patients.
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AI analysis of surgeons' techniques during coronary artery bypass grafting
We will see if an AI program can score surgeons' stitching technique during left anterior descending artery bypass in adults having their first isolated CABG.
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AI model to predict hidden lymph node cancer in lung patients
This study is testing a new AI tool to see if it can find hidden cancer in lymph nodes for people with early-stage lung cancer to help doctors make better treatment choices.
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Comparing a sensorized treadmill and conventional therapy for balance disorders
This study tests whether using a special treadmill can help older adults with balance problems stay safer and improve their daily activities better than regular group therapy.
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Using AI to identify and prevent smoking-related diseases
This study is testing a new AI tool to see if it can help find and tell the difference between harmful and harmless lung nodules in smokers and former smokers over 50 who are at high risk for lung cancer.
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Using AI to diagnose melanoma in young patients
This study is testing if artificial intelligence can help doctors better identify melanoma in children and young adults by looking at skin images.
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Registry collecting imaging data for patients with atrial fibrillation
This study is collecting imaging data from patients with atrial fibrillation to see if artificial intelligence can help predict blood clots in the heart before they undergo treatment.
NIH-funded research (10)
Early-stage science funded by the US National Institutes of Health. Most of these projects don't enroll patients, but they show what is being worked on.
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Addressing fairness in AI models for asthma in young children
This grant aims to ensure AI tools used for diagnosing and managing asthma in children aged 0-11 work fairly for all socioeconomic and demographic groups.
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Using AI and drug modeling to understand why genes and other medicines change clopidogrel response
This project uses AI, genetic data, and drug-response models to find why people with different genes or taking other medications respond differently to clopidogrel.
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AI-powered tools to improve periodontal diagnosis and treatment decisions
A dental AI tool helps doctors diagnose periodontitis more accurately and tailor care for adults, using 2D/3D images and health records.
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Data and AI Core for Cardiovascular and Metabolic Health (Core D)
A central data and AI hub at the University of Louisville will help researchers collect, harmonize, and analyze data to understand how nutrition, metabolism, and heart health influence disease.
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Making asthma care AI work fairly for all children
This project aims to improve AI tools used in pediatric asthma care so they give fairer and more reliable results for children from different incomes and backgrounds.
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Using AI to improve safety in radiation therapy treatment planning
This study is testing a new AI tool to help doctors in radiation therapy work together better and make fewer mistakes before starting treatment, all to keep patients safer and improve their care.
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Using artificial intelligence to improve treatment planning for patients in end-of-life care
This study is exploring how artificial intelligence can help doctors create personalized care plans for patients in end-of-life and palliative care, making sure that treatment choices reflect what patients and their families want while also looking at any concerns about fairness and patient control.
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Using AI to enhance animal care and monitoring systems at Rutgers University
This study is all about making animal homes at Rutgers University better by using smart technology that keeps an eye on their health and living conditions, helping researchers and caretakers take even better care of them.
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Using AI software to diagnose retinopathy of prematurity in infants
This study is testing a smart computer program that helps doctors quickly and accurately check for a serious eye condition in premature babies, with the goal of preventing blindness and making sure the program works safely in real-life situations.
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Exploring the use of artificial intelligence in healthcare
The AI Summit is a friendly gathering where healthcare leaders, including FDA experts, come together from 2022 to 2026 to talk about how to use artificial intelligence to improve patient care and make healthcare better for everyone.
Related topics
Quick answers
How many Artificial Intelligence (AI) clinical trials are recruiting right now?
43, as of November 12, 2026. 1 of them was first registered in the last 30 days. We update this list each time we refresh our data from ClinicalTrials.gov.
Where are these trials running?
In 19 countries. The most sites are in China (13 trials), Taiwan (5 trials), Italy (5 trials), Czechia (2 trials), Poland (2 trials). Each study page lists its sites and which ones are recruiting.
What phases are they in?
Phase 4: 1. Trials with no phase listed are usually device, behavioural or observational studies.
How do I join one?
Open a study, check the "Is this trial a fit for you?" section, then contact the study team listed on the page. They will ask a few screening questions. Asking is free and does not commit you to anything. Talk it over with your doctor first.
Find the studies that fit you
A list is a starting point. Tell us your situation in your own words and we'll rank the studies that match and explain why. It's free and needs no account.