Clinical trials: Artificial Intelligence (AI) in Diagnosis
Locally Advanced Rectal Cancer (LARC)
AI-Based Prediction of Pathological Response in Rectal Cancer Patients Receiving Total Neoadjuvant Therapy
This study aims to better understand how body composition, inflammation, and nutrition affect how rectal cancer responds to treatment.
- Trial name
- CINR-AI (NCT07049627)
- Testing
- Total Neoadjuvant Therapy (TNT)
- Where
- 2 sites in Turkey (Türkiye)
- Volunteers
- 93 people
- Sponsor
- Ankara Etlik City Hospital
Mechanical Ventilation, Patient-Ventilator Asynchrony
Patient-Ventilator Asynchrony: Occurence and Clinical Impact in Usual Care
The goal of this observational study is to unravel the occurence, impact and relations of Patient-Ventilator Aynchrony (PVA) in mechanically ventilated patients.
- Trial name
- PVA-detection (NCT07624786)
- Testing
- PVA classification software
- Where
- 3 sites in Netherlands
- Volunteers
- 110 people
- Sponsor
- Erasmus Medical Center
Heart Failure
Point of Care Artificial Intelligence Tool for Heart Failure Diagnosis
Abbreviations/acronyms: DUO-EF = prediction of ejection fraction (EF) using the Eko-DUO digital stethoscope algorithm HF = heart failure HFrEF = heart failure with reduced ejection fraction COVID-19 = coronavirus disease 2019 Eko…
- Trial name
- DUO-EF-19 (NCT04601415)
- Testing
- ECG from handheld device
- Where
- United Kingdom
- Volunteers
- 1,050 people, healthy volunteers welcome
- Sponsor
- Imperial College London
Critical Illness, Sepsis
Point-of-Care AI Assistance and Critical Care Outcomes: A Randomized Trial
This is a prospective, unmasked, randomized, multicenter clinical trial evaluating the impact of point-of-care large language model (LLM)-based decision support on diagnostic accuracy and clinical outcomes in adult medical…
- Conditions
- Critical Illness, Sepsis, Acute Respiratory Failure (ARF), Multi-organ Failure
- Trial name
- POC-AI-ICU (NCT07293078)
- Testing
- Point-of-care large language model decision support (ChatGPT-5)
- Where
- United States
- Volunteers
- 1,000 people
- Sponsor
- MetroWest Artificial Intelligence Research Workgroup
Hyperkalemia
A Study to Detect Hyperkalemia Using Smartphone-enabled Electrocardiogram (EKG)
The purpose of this study is to validate the real-world performance of a previously developed Artificial Intelligence - Electrocardiogram (AI-ECG) algorithm for identification of hyperkalemia with a six-lead mobile-enhanced…
- Trial name
- REACT (NCT05441852)
- Where
- United States
- Volunteers
- 1,151 people
- Sponsor
- Mayo Clinic
Skin Condition, Dermatology
Application of the Belle.AI Dermatological Image Reference System for Patient Diagnosis in an Active Clinical Setting
The goal of this research study is to test a new, investigational tool that uses artificial intelligence (AI) to help primary care providers assess skin conditions.
- Conditions
- Skin Condition, Dermatology, Dermatology/Skin - Other
- Trial name
- NCT06724627
- Testing
- Dermatology/Skin - Other
- Where
- United States
- Volunteers
- 263 people
- Sponsor
- BelleTorus Corporation
Sleep Wake Disorders, Sleep Initiation and Maintenance Disorders
AI-Powered Sleep Hygiene Mentor for Adults Living With HIV
Poor sleep is common among people living with HIV and is linked to fatigue, psychological distress and poorer adherence to antiretroviral therapy.
- Conditions
- Sleep Wake Disorders, Sleep Initiation and Maintenance Disorders, HIV Infections
- Trial name
- NCT07894042
- Testing
- AI-powered sleep hygiene mentor
- Where
- Indonesia
- Volunteers
- 100 people
- Sponsor
- Universitas Indonesia
Stroke, Acute, Apoplexy; Brain
Artificial Intelligence (AI) Support in Medical Emergency Calls
More than 12.000 patients suffer acute stroke in Norway every year, but less than half of them reach hospital within the current treatment window for thrombolysis.
- Conditions
- Stroke, Acute, Apoplexy; Brain, Emergencies, Communication, Multidisciplinary
- Trial name
- AISMEC (NCT04648449)
- Testing
- Artificial intelligence on emergency calls
- Where
- Norway
- Volunteers
- 1,000 people
- Sponsor
- Haukeland University Hospital
Dental Plaque
Comparative Accuracy of AI Models and Clinical Assessment for Dental Plaque Detection in Children
This diagnostic accuracy study aims to evaluate the effectiveness of various artificial intelligence models in detecting dental plaque from intraoral images compared to clinical assessments performed by dentists among children.
- Trial name
- NCT06760104
- Testing
- Dental Plaque Detection Using AI Models
- Where
- Egypt
- Volunteers
- 323 people
- Sponsor
- Naema Ahmed
Cardiomyopathy
AI-SCREENDCM Decentralized Clinical Trial - Pilot Study
The purpose of this study is to assess the feasibility and impact of screening FDR of DCM probands using a mobile ECG with the ability to transmit the ECG for cloud-based AI analysis to detect reduced left ventricular ejection…
- Trial name
- NCT06609174
- Testing
- KardiaRx ECG Screening and AI interpretation of ECG
- Where
- United States
- Volunteers
- 119 people
- Sponsor
- Mayo Clinic
Colorectal Neoplasms, Colonic Polyp
Adenoma Detection Rate Using AI System in China
The primary aim of this study is to explore the usefulness of Artificial Intelligence system in colonoscopy on adenoma detection rate (ADR). Other aims include to explore the data below when Artificial Intelligence is used.
- Conditions
- Colorectal Neoplasms, Colonic Polyp, Adenoma
- Trial name
- SinoAIADR (NCT03840590)
- Testing
- CSK AI system, Standard Colonoscopy
- Where
- 4 sites in China
- Volunteers
- 743 people, healthy volunteers welcome
- Sponsor
- Changhai Hospital
Osteoarthritis, Osteoarthritis of the Hip or Knee
Conversations in Health Literacy Using AI Technology for Osteoarthritis Patients
The goal of this clinical trial is to assess the use of a generative artificial intelligence large language model chatbot in improving decision making factors in patients with hip and knee osteoarthritis.
- Trial name
- CHAT-OA (NCT06778486)
- Testing
- Artificial Intelligence Chatbot
- Where
- United States
- Volunteers
- 100 people
- Sponsor
- University of California, Davis
Lung Carcinoma, Lung Non-Small Cell Carcinoma
Using an Artificial Intelligence Software Tool (iSeg) During Radiation Treatment Planning for Patients With Lung Tumors
This clinical trial studies whether an artificial intelligence (AI) software tool called iSeg can be safely and effectively used during routine radiation treatment planning for patients with lung tumors.
- Conditions
- Lung Carcinoma, Lung Non-Small Cell Carcinoma, Metastatic Malignant Neoplasm in the Lung
- Trial name
- NCT07898241
- Testing
- Artificial Intelligence-based Intervention, Best Practice, Computed Tomography
- Where
- United States
- Volunteers
- 34 people
- Sponsor
- Northwestern University
Normal Labor
Generative AI-Powered Intrapartum Clinical Decision Support Among Healthcare Providers
Pregnancy and childbirth are uniquely important events in women's lives because they are accompanied by major physical, emotional, and psychological changes.
- Trial name
- NCT07720531
- Testing
- Generative AI-Powered Intrapartum Chatbot
- Where
- Egypt
- Volunteers
- 427 people, healthy volunteers welcome
- Sponsor
- Delta University for Science and Technology
Type 2 Diabetes Mellitus (T2DM), Cardiovascular Diseases
Cardioprotective Effects of SGLT2 Inhibitors and GLP-1 Receptor Agonists in Korean Patients With Type 2 Diabetes
This observational study will evaluate the cardiovascular effects of sodium-glucose cotransporter-2 inhibitors (SGLT2 inhibitors) and glucagon-like peptide-1 receptor agonists (GLP-1 receptor agonists) in Korean adults with type…
- Conditions
- Type 2 Diabetes Mellitus (T2DM), Cardiovascular Diseases, Stage B Heart Failure
- Trial name
- NCT07770737
- Where
- South Korea
- Volunteers
- 100 people
- Sponsor
- Dongtan Sacred Heart Hospital
Melanoma (Skin Cancer), Artificial Intelligence (AI)
Artificial Intelligence Based Melanoma Early Diagnosis and Risk Prediction in Children, Adolescents and Young Adults
The goal of this study is to develop supportive diagnostic artificial intelligence algorithms to distinguish melanoma from nevi or other benign pigmented skin lesions, especially in younger patients (below the age of 30).
- Conditions
- Melanoma (Skin Cancer), Artificial Intelligence (AI), Pediatric Cancer
- Trial name
- AI-MEL (NCT06621810)
- Where
- 3 sites in Germany, Italy and 1 more
- Volunteers
- 3,000 people, healthy volunteers welcome
- Sponsor
- German Cancer Research Center
Post-acute COVID-19 Syndrome
SENSING-AI Cohort for Long COVID Patients
The prospective study will focus on the collection of biometric and psychometric data from a limited population for 1 month with the aim of complementing the SENSING-AI retrospective cohort.
- Trial name
- SENSING-AI (NCT05204615)
- Testing
- Collection of clinical, psychometric and biometric data
- Where
- 2 sites in Spain
- Volunteers
- 10 people
- Sponsor
- Adhera Health, Inc.
Breast Cancer
Artificial Intelligence (AI)-Based Personalized Exercise Coaching for Patients With Breast Cancer
This prospective, single-center, randomized controlled trial aims to evaluate the effectiveness and safety of an artificial intelligence (AI)-based personalized exercise coaching system in female breast cancer survivors who have…
- Trial name
- NCT07844941
- Testing
- AI-Based Personalized Exercise Coaching, Conventional Exercise Guidance
- Where
- China
- Volunteers
- 60 people
- Sponsor
- Shanghai Jiao Tong University School of Medicine
Small for Gestational Age Infant, Fetal Growth Restriction
Developing and Testing AI Models for Fetal Biometry and Amniotic Volume Assessment in Fetal Ultrasound Scans.
Routine fetal ultrasound scan during the second trimester of the pregnancy is a low-cost, noninvasive screening modality that has been proven to lower fetal mortality by up to 20%.
- Conditions
- Small for Gestational Age Infant, Fetal Growth Restriction, Oligohydramnios, Polyhydramnios
- Trial name
- NCT05059093
- Testing
- Classification and segmentation deep learning models
- Where
- 6 sites in Morocco
- Volunteers
- 122 people, healthy volunteers welcome
- Sponsor
- Deepecho
Gastric Cancer Adenocarcinoma Metastatic, Lymph Node Metastasis
AI-Based Prediction of Lymph Node Metastasis in Gastric Cancer Using Preoperative Multimodal Data
This study aims to develop and validate an artificial intelligence (AI) system that can predict whether lymph node metastasis has occurred in patients with gastric cancer before surgery.
- Conditions
- Gastric Cancer Adenocarcinoma Metastatic, Lymph Node Metastasis, Artificial Intelligence (AI) in Diagnosis
- Trial name
- NCT06957678
- Testing
- Artificial Intelligence-Based Predictive Model for Lymph Node Metastasis
- Where
- China
- Volunteers
- 1,200 people
- Sponsor
- Qun Zhao