Clinical trials
Deep Learning clinical trials
Below are recruiting deep learning clinical trials, each written for real people, not researchers. We’re tracking 86 recruiting studies, each written for real people, not researchers, below.
Recruiting studies
- NCT06463444RecruitingPhase 1
Precision treatment for inoperable liver cancer
This trial tests a new precision approach for people with liver cancer that cannot be removed by surgery. It uses a computer model to analyze your tumor and genetic information to see if combining HAIC (chemotherapy directly into the liver), lenvatinib (a targeted drug), and a PD-1 inhibitor (immunotherapy) is the right treatment for you.
Wuhan, HubeiAges 18–75 - NCT07392567Recruiting
AI predicts liver spread in colorectal cancer
This study tests whether an artificial intelligence (AI) model can predict if colon or rectal cancer will spread to the liver. You will have a CT scan before surgery, and the AI will analyze the scan to see if it can forecast future liver metastasis.
Wuhan, HubeiAges 18–75 - NCT07274423Recruiting
Deep learning for clearer ankle MRI scans
This study tests if a new deep learning technology can improve the quality of ankle MRI images. It may help people with ankle injuries get a more accurate diagnosis.
Wuhan, HubeiAges 18 years+ - NCT06831357Recruiting
Predicting Cancer Spread in Nasopharyngeal Cancer Using AI
This trial uses a deep learning computer model to look at tissue images and MRI scans to predict whether nasopharyngeal carcinoma may spread to other parts of the body. It may help doctors decide on the best treatment for people with certain stages of this cancer.
Guangzhou, GuangdongAges Any age - NCT06540846Recruiting
Deep learning study for gynecologic muscle tumors
This trial uses a computer to study tissue samples from uterine muscle tumors (like fibroids and rare cancers). The goal is to improve how doctors classify these tumors and predict patient outcomes.
BordeauxAges Any age - NCT07162168Recruiting
Using AI to measure bone age from abdominal CT scans
This study uses artificial intelligence to estimate bone age from standard abdominal CT scans. It may help researchers understand how bone age relates to health conditions without extra X-rays.
BeijingAges 18 years+ - NCT07127939Recruiting
AI eye test for traditional Chinese medicine body type
This study uses eye photos and artificial intelligence to figure out your traditional Chinese medicine body type. It may help doctors understand your health better without extra poking or prodding.
Nanchang, JiangxiAges 18–45 - NCT06839443Recruiting
AI to detect hydroxychloroquine eye damage
This study uses artificial intelligence to look at eye images of people who have taken hydroxychloroquine for a long time. The goal is to better detect or predict early signs of retinal damage, so you can get the right care sooner.
PortugalAges 18–100 - NCT06810349Recruiting
Using AI to find cancer origin from lymph node biopsy
This study uses computer intelligence (deep learning) to analyze cells from a lymph node biopsy to find where in the body a cancer might have started. It looks at past patient data and images to train a program that could help doctors in the future.
Chengdu, SichuanAges Any age - NCT06965387Recruiting
Deep learning study for gummy smile analysis
This study uses artificial intelligence to analyze smiles and identify a gummy smile (excess gum showing when you smile). It may help researchers better understand and diagnose this condition.
Ankara, CankayaAges 12 years+ - NCT07399236Recruiting
AI prediction of liver spread in colorectal cancer
This study looks at whether an AI tool can predict if colorectal cancer will spread to the liver. The researchers will review past medical records of patients who had surgery to remove their cancer and had no signs of spread at that time.
Wuhan, HubeiAges 18–75 - NCT07739628Enrolling by invitation
Testing a computer tool for osteoporosis screening from CT scans
This study checks if a new computer program can find people at risk for osteoporosis more easily, using CT scans you already had. If you are found to be high risk, you'll get a free bone density test (DXA) to confirm, and help improve this tool.
Wuhan, HubeiAges 18 years+ - NCT04749927Recruiting
Image-based eye photos to study heart blood-vessel risks
This study uses deep learning (computer pattern recognition) to analyze retinal photos (pictures of the eye’s blood vessels). It aims to link what’s seen in the eye to heart and blood-vessel disease patterns, especially in people with higher cardiovascular risk.
SeoulAges 20–79 - NCT04921020Recruiting
Deep learning study of eyelid movement and eyelid shape
This study uses a computer method to measure your eyelid shape and how your eyelid moves over time. It may help doctors better assess eyelid problems such as drooping or spasms using images or video.
Hangzhou, ZhejiangAges Any age - NCT05140889Recruiting
AI helps predict asthma severity in children
This trial studies an AI (computer) model that uses CT scan images plus health and blood/clinical information to predict how severe asthma is in children. It may help doctors better understand your child’s asthma severity and tailor care.
PaviaAges 6–17 - NCT05204186Recruiting
AI Tool to Predict Health Outcomes After Bladder Removal Surgery
This study tests an artificial intelligence tool designed to predict how patients will recover after bladder cancer surgery. The AI analyzes existing medical information to help doctors better understand which patients might face complications based on their other health conditions.
Amiens, PicardieAges 18 years+ - NCT05317390Recruiting
Tests an AI tool to diagnose isolated dystonia
This trial checks whether an AI (software) called DystoniaNet can accurately identify isolated dystonia using information from your evaluation, and compares its results to standard diagnosis. If you have focal, segmental, or generalized dystonia, this study may help improve faster and more accurate diagnosis in the future.
Boston, MassachusettsAges Any age - NCT05426135Recruiting
AI tool to assess cancer risk and guide care
This study tests an artificial intelligence (AI) system that uses your health information and medical images to better judge cancer risk and support diagnosis and treatment decisions. It may help doctors make more consistent assessments by combining clinical records, imaging, and other lab-style data.
Wuhan, HubeiAges 18–75 - NCT05792267Recruiting
AI system for pancreas scans during endoscopic ultrasound
This trial tests a new computer (deep-learning) system to help analyze pictures from an endoscopic ultrasound scan of the pancreas. It may improve how the scan is done or interpreted, depending on study results.
Changsha, HunanAges 18–80 - NCT05792280Recruiting
AI-assisted endoscopic ultrasound for chest (mediastinal) imaging
This study tests a new computer (deep-learning) system to help interpret images from an endoscopic ultrasound exam of the chest area. It may help make the scan information more consistent and useful for diagnosis.
Changsha, HunanAges 18–80 - NCT05800821Recruiting
Predicting brain blood-flow problems after carotid surgery
This study uses deep learning to predict which people are at risk for “cerebral hyperperfusion syndrome” (a dangerous spike in brain blood flow) after carotid revascularization. If you qualify, they’ll use scans/tests to estimate your risk so doctors can watch you more closely if needed.
MinskAges 30–80 - NCT05925764Recruiting
AI tool to help grade lung adenocarcinoma biopsies
This trial tests an artificial intelligence (AI) method that reads whole slide pathology images to classify how aggressive your lung adenocarcinoma is. It may help doctors diagnose the lung cancer grading system more accurately using existing lab slides after surgery.
Zunyi, GuizhouAges 18–85 - NCT06088134Recruiting
Predicting survival after kidney cancer surgery with CT scans
This study uses a computer model to analyze your CT scans and predict how long you might stay cancer-free after surgery. It aims to help doctors personalize follow-up care for clear cell kidney cancer.
Chongqing, Chongqing MunicipalityAges Any age - NCT06118840Recruiting
AI tool for spotting brain aneurysms on CT scans
This trial tests if an AI model can help doctors detect brain aneurysms more accurately on head CT angiograms (CTA). It may lead to earlier treatment and better outcomes.
Hefei, AnhuiAges 18 years+
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Common questions
- Are there clinical trials for deep learning?
- Yes. Clin2 currently lists 86 recruiting deep 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 deep 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 deep 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.