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
- NCT07373951Enrolling by invitation
Predicting cancer gene status from MRI scans in brain metastasis
This trial uses brain MRI scans and deep learning to predict whether non-small cell lung cancer that has spread to the brain has certain gene changes (EGFR or ALK). Knowing this may help guide treatment without needing additional tissue testing.
Beijing, Beijing MunicipalityAges 18 years+ - NCT06749145Enrolling by invitation
Using deep learning to find aortic stenosis earlier
This study tests if a deep learning tool can help detect aortic stenosis, a heart valve condition, in older adults during routine primary care visits. If you are 70 or older and have not had a recent echocardiogram, you may be able to join.
New Haven, ConnecticutAges 70 years+ - NCT06444425Enrolling by invitation
AI test for heart function using ultrasound
This trial uses artificial intelligence to analyze heart ultrasound images. It aims to see if AI can detect heart function better than standard methods. You may be eligible if you are a cardiology patient having an ultrasound and can return for extra blood pressure checks.
Yiwu, ZhejiangAges 18 years+ - NCT07738419Recruiting
AI Heart Ultrasound Measurement Accuracy Study
This study tests an artificial intelligence program designed to automatically take measurements from standard heart ultrasound images. It aims to see if the AI works as well as expert doctors.
Milan, LombardyAges 18 years+ - NCT07559123Recruiting
Imaging to predict who benefits from chemoimmunotherapy before lung cancer surgery
This study uses CT scan images to help doctors predict which patients with resectable lung cancer will benefit most from receiving chemoimmunotherapy (a combination of chemotherapy and immunotherapy) before surgery. The goal is to personalize treatment planning and improve outcomes.
SeoulAges 18 years+ - NCT06463392Recruiting
Deep learning tool to diagnose post-radiation nasopharyngeal changes
This trial tests a new computer-based tool (deep learning) to help diagnose a condition called sbORN (suspected benign or recurrent nasopharyngeal carcinoma) after radiation therapy. It aims to see if the tool can accurately tell if a suspicious spot is a recurrence or something harmless.
Guangzhou, GuangdongAges 18 years+ - NCT06735118Recruiting
Can AI help see chemo-related fatty liver?
This study uses a special MRI technique and artificial intelligence to see how chemotherapy may cause a fatty liver. It may help find liver changes early in people who have had chemo.
Kunming, YunnanAges 18–80 - NCT07235410Recruiting
Body composition study for liver cancer patients having TACE
This trial uses deep learning to analyze body composition from scans in people with hepatocellular carcinoma (HCC) who are undergoing TACE (a treatment that blocks blood flow to the tumor). It aims to predict outcomes better and may help doctors tailor care.
Wuhan, HubeiAges 18 years+ - NCT07274436Recruiting
Deep learning in heart MRI scans
This study uses artificial intelligence to improve the quality of heart MRI images. It may help doctors get clearer pictures of your heart.
Wuhan, HubeiAges 18 years+ - NCT07551375Recruiting
Fast MRI scan to diagnose gallbladder inflammation
This study tests whether a new type of quick MRI scan can reliably detect acute cholecystitis—sudden inflammation of the gallbladder. If it works well, doctors may be able to diagnose this condition faster and help patients get treatment sooner.
Beijing, Beijing MunicipalityAges 18 years+ - NCT06749132Enrolling by invitation
AI-powered monitoring for mild aortic valve disease
This study uses an artificial intelligence (AI) program to analyze past heart ultrasound images and predict if your aortic valve condition (mild thickening or narrowing) may get worse over time. The goal is to catch changes early and personalize your follow-up care.
New Haven, ConnecticutAges 65 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 - NCT06842446Recruiting
Fast detection of blood clots using machine learning
This trial tests whether a machine learning algorithm can quickly detect deep vein thrombosis (blood clots) in people coming to the emergency room. It could help speed up diagnosis and treatment.
SarpsborgAges 18 years+ - NCT07455760Recruiting
Deep brain stimulation and speech sequencing study
This study looks at how deep brain stimulation affects speech in people with Parkinson's disease or essential tremor. It tests whether the stimulation changes the way you say sequences of sounds.
Boston, MassachusettsAges 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.