Learning Clinical Trials

1 recruiting

Frequently Asked Questions

Common questions about Learning clinical trials

A clinical trial is a carefully designed research study that tests new medical treatments, drugs, devices, or approaches in human volunteers. Every approved medication and treatment available today was proven safe and effective through clinical trials.

All clinical trials are reviewed and approved by Institutional Review Boards (IRBs) — independent committees that evaluate patient safety. Trials follow strict protocols, and your health is monitored closely throughout. You can withdraw at any time.

Not necessarily. Many trials compare the new treatment against the current standard of care, meaning all participants receive active treatment. When placebos are used, they are typically combined with standard treatment, not given alone. The trial description will always specify the design.

Under the Affordable Care Act, most private insurers are required to cover routine patient care costs during a clinical trial. The sponsor typically covers the investigational treatment itself. Medicare also covers routine costs for qualifying trials.

Yes. Participation is completely voluntary. You can withdraw at any time, for any reason, without it affecting your access to standard medical care.

Each trial has specific eligibility criteria — including age, diagnosis, disease stage, prior treatments, and general health. Browse the trials listed above and check their eligibility sections. You can also contact the trial site directly to discuss your situation.

Showing 116 of 16 trials

Recruiting
Not Applicable

The Effect of Game-Based Learning on Identifying Cognitive Distortions and Interpersonal Communication Competence in Nursing Students' in the Care of Anxious Individuals

Game Based Learning
Necmettin Erbakan University80 enrolled1 locationNCT07442331
Recruiting

Remote Monitoring of Asthma in Children and Young People

Asthma AttackAsthma ChildhoodRemote Monitoring+2 more
University of Edinburgh900 enrolled1 locationNCT07129616
Recruiting
Not Applicable

Effects of Exercise and Sleep on Motor Learning and Functional Abilities in Multiple Sclerosis

ExerciseSleepMultiple Sclerosis+2 more
Zealand University Hospital20 enrolled2 locationsNCT07304375
Recruiting

Deep Learning for Automated Discrimination Between Stage T1-T2 and T3 Renal Cell Carcinoma on Contrast-Enhanced CT

Carcinoma, Renal CellPathologyDeep Learning+1 more
Peking University First Hospital1,000 enrolled1 locationNCT07166445
Recruiting
Not Applicable

Remediation Program Via a "Serious Game" for the Cognitive Functions of Multiple Sclerosis Patients

Multiple SclerosisMemoryLearning
Lille Catholic University150 enrolled6 locationsNCT04694534
Recruiting

Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound: A Multicenter, Ambispective Cohort Study

Bladder CancerUltrasoundDeep Learning
Peking University First Hospital400 enrolled1 locationNCT07111364
Recruiting
Not Applicable

Interventions in Mathematics and Cognitive Skills

Cognitive ChangeCognitive DysfunctionDecision Making+25 more
Stanford University180 enrolled1 locationNCT05201534
Recruiting

Deep Learning Model Predicts Pathological Complete Response of Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunochemotherapy

Esophageal Squamous Cell CarcinomaPathological Complete ResponseDeep Learning+1 more
Tongji Hospital300 enrolled1 locationNCT07088354
Recruiting

Bladder Cancer Staging and Prediction of New Adjuvant Chemotherapy Efficacy Based on Deep Learning and Transfer Learning in Ultrasound-Magnetic Resonance-Pathology Multimodal Multiscale

Bladder CancerNeoadjuvant ChemotherapyDeep Learning+2 more
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University480 enrolled1 locationNCT07051083
Recruiting
Not Applicable

Deep Learning Using Chest X-Rays to Identify High Risk Patients for Lung Cancer Screening CT

Lung CancerDeep LearningHealth Screening+1 more
Massachusetts General Hospital1,500 enrolled1 locationNCT06910956
Recruiting

Validation of the Prognostic Impact of a Retinal Photograph-based Cardiovascular Disease Risk Stratification System in de Novo HFrEF

Heart FailureCardiomyopathiesDeep Learning+2 more
Yonsei University100 enrolled1 locationNCT06978998
Recruiting

Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis

Gastric CancersEsophageal CancerCancer Screening+14 more
Second Affiliated Hospital, School of Medicine, Zhejiang University600 enrolled4 locationsNCT06822413
Recruiting

Development and Demonstration of Intelligent Assessment Based on Multi-modal Information Fusion for Tumor Risk and Diagnosis and Treatment

Lung CancerColon CancerStomach Cancer+6 more
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology3,000 enrolled1 locationNCT06653478
Recruiting

Implementation of Surgical Safety and Intraoperative Metastasis Identification Through Deep Learning: Multicentric Video Collection for Minimally Invasive Sentinel Lymph Node Dissection in Uterine Malignancies

Cervical CancerEndometrial CancerArtificial Intelligence+1 more
Fondazione Policlinico Universitario Agostino Gemelli IRCCS100 enrolled2 locationsNCT06619002
Recruiting

National Robotics-Assisted Radical Prostatectomy Database

Prostate CancerPatient Reported Outcome MeasuresRobotic-Assisted Radical Prostatectomy+4 more
Melbourne Health10,000 enrolled8 locationsNCT06279260
Recruiting

Artificial Intelligence System for Assessment of Tumor Risk and Diagnosis and Treatment

Lung CancerColon CancerStomach Cancer+6 more
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology3,000 enrolled1 locationNCT05426135