Clinical trials: AI
AI (Artificial Intelligence), Mammary Cancer
Experiment on the Use of Innovative Computer Vision Technologies for Analysis of Medical Images in the Moscow Healthcare System
It is planned to integrate various services based on computer vision technologies for analysis of the certain type of x-ray study into Moscow Unified Radiological Information Service (hereinafter referred to as URIS).
- Conditions
- AI (Artificial Intelligence), Mammary Cancer, Lung Cancer, X-Rays; Lesion
- Trial name
- NCT04489992
- Where
- Russia
- Volunteers
- 133,000 people, healthy volunteers welcome
- Sponsor
- Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department
Balance Disorders, Rehabilitation
Identify the Most Effective Rehabilitation Method Between a Treatment with a Sensorized Treadmill (Walker View) and a Treatment with Conventional Group Therapy in Balance Disorders and the Use of Artificial Intelligence to Identify Predictive Indices to Prevent Falls and Diagnose Promptly the Risk
Falls in the elderly are one of the main sources of disability and hospitalization, with a significant impact on quality of life and social and healthcare costs.
- Conditions
- Balance Disorders, Rehabilitation, Falls, Falls Prevention
- Trial name
- UAI (NCT06649500)
- Testing
- Treadmill, conventional therapy
- Where
- Italy
- Volunteers
- 108 people
- Sponsor
- Fondazione Policlinico Universitario Campus Bio-Medico
Artifical Intelligence, Nursing Education
AI-SUPPORTED FLIPPED LEARNING IN BREAST SELF-EXAMINATION TRAINING
The global increase in cancer cases has made breast cancer the second most common cancer after lung cancer and a primary health problem among women.
- Conditions
- Artifical Intelligence, Nursing Education, Breast Self-Examination
- Trial name
- NCT07562321
- Testing
- Artificial Intelligence-Supported Flipped Learning Model-Based Breast Self-Examination Training
- Where
- Turkey (Türkiye)
- Volunteers
- 80 people, healthy volunteers welcome
- Sponsor
- Baskent University
Major Depressive Disorder
Optimize and Predict Antidepressant Efficacy for Patient With MDD Using Multi-omics Analysis and AI-predictive Tool
OPADE is a non-profit, observational, multicenter, open-label study aimed at defining personalized treatment for Major Depressive Disorder (MDD).
- Trial name
- OPADE (NCT06550037)
- Where
- Italy
- Volunteers
- 350 people
- Sponsor
- Alessio Fasano
Acute Febrile Illness, Bacterial Infections
AI-Guided Proteomic Biomarker Panel for Differentiating Bacterial and Viral Infections in Acute Febrile Illness
This study is a proteomics-based diagnostic biomarker study conducted on the same patient cohort as the transcriptomic biomarker study (NCT065529754).
- Conditions
- Acute Febrile Illness, Bacterial Infections, Viral Infections, Sepsis
- Trial name
- NCT07205575
- Testing
- Proteomic Biomarker Panel
- Where
- China
- Volunteers
- 394 people
- Sponsor
- Qilu Hospital of Shandong University
Breast Cancer, Colorectal Cancer
AI-Assisted Chemotherapy Side Effect Management
This two-stage adaptive randomized controlled trial evaluates the feasibility and preliminary efficacy of large language model (LLM)-assisted intervention for managing chemotherapy side effects in patients with solid tumors.
- Trial name
- ALLIANCE (NCT07198581)
- Testing
- LLM-assisted chemotherapy side effect management
- Where
- South Korea
- Volunteers
- 174 people
- Sponsor
- Incheon St.Mary's Hospital
Nursing Students, Artificial Intelligence (AI)
Exploring Nursing Students' Ability to Create Artificial Intelligence-Enhanced Patient Education Materials on Infection Care
The purpose of this study is to explore the ability of nursing students to create artificial intelligence-supported patient education materials regarding infection care.
- Conditions
- Nursing Students, Artificial Intelligence (AI), Patient Education Materials, Randomized Controlled Trial
- Trial name
- NCT06983236
- Testing
- AI-enabled patient education material, Traditional patient education material
- Volunteers
- 110 people, healthy volunteers welcome
- Sponsor
- Çankırı Karatekin University
Chronic Respiratory Failure, Acute Respiratory Failure
Validation Study of the EMILY AI Device in Acute and Chronic Respiratory Failure
Currently, there is no holistic solution for patients with respiratory diseases that includes oxygenation and management of a patient with respiratory disease, combining dynamic and automatic O2 administration and the detection…
- Trial name
- NCT06952816
- Testing
- Emily.AI
- Where
- 2 sites in Spain
- Volunteers
- 20 people
- Sponsor
- Aether Tech S.L.
Endoscopy, Digestive System
The Impact of Artificial Intelligence (AI) on the Quality of Upper Gastrointestinal (GI) Endoscopy
Oesophageal and gastric cancer are two of the six less survivable cancers, responsible for half of cancer deaths and a quarter of cancer cases.
- Trial name
- NCT05845463
- Testing
- Cerebro endoscopy quality control tool
- Where
- United Kingdom
- Volunteers
- 300 people, healthy volunteers welcome
- Sponsor
- Sandwell & West Birmingham Hospitals NHS Trust
Cancer
Glasgow Low-dose CT and AI-based Diagnostics to Case Find Lung Cancer and Other Cardio-respiratory Long-term Conditions - Feasibility Study
Lung cancer is one of the most common and serious cancers in Scotland and is often diagnosed at a late stage. Early detection is crucial to improving survival rates.
- Trial name
- GALACTIC-1 (NCT07372508)
- Testing
- Low dose Chest CT
- Where
- United Kingdom
- Volunteers
- 500 people
- Sponsor
- NHS Greater Glasgow and Clyde
Lmbar Spine With Screws
AI Based Metal Artifact Reduction-PMAR
The study is going to enroll about 220 consecutive patients with screws in lumber spine after internal fixation surgery who underwent follow-up assessment using Incisive CT according to the department standard of care.
- Trial name
- NCT07619404
- Volunteers
- 220 people
- Sponsor
- Philips Clinical & Medical Affairs Global
Hypopharyngeal Cancer, Laryngeal Cancer
A Machine Learning-Based Risk Prediction Model for Head and Neck Cancerous Lesions
This study aims to develop and validate a clinical prediction model for the risk of head and neck cancerous lesions using deep learning combined with AI algorithms, based on multi-center clinical data.
- Conditions
- Hypopharyngeal Cancer, Laryngeal Cancer, Head and Neck Cancer
- Trial name
- ML-HNC-Risk (NCT07532538)
- Where
- China
- Volunteers
- 3,000 people, healthy volunteers welcome
- Sponsor
- The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
Postoperative Complications, Cardiovascular Diseases
Comparing Traditional Risk Scores and an AI-Based Multimodal Model for Predicting Cardiovascular Events After Gastrointestinal Surgery
The goal of this observational study is to develop and evaluate an artificial intelligence (AI)-based multimodal model for predicting major cardiovascular events within 30 days after gastrointestinal surgery in adults at Bach Mai…
- Conditions
- Postoperative Complications, Cardiovascular Diseases, Digestive System Surgical Procedures
- Trial name
- GI-MACE-AI (NCT07539532)
- Where
- Vietnam
- Volunteers
- 5,000 people
- Sponsor
- Bach Mai Hospital
Healthy Population (HP)
High-quality Image (NIR and RGB) Dataset Synchronized With Contact Vital Sings Recordings and Clinical Data of Stratified Healthy Population. Algorithms and AI Models to Obtain a Set of Vital Signs Image-based.
The objective of this study is to collect an image dataset of healthy and pathological population with a characterization of the potential factors that may influence the methodologies used to obtain vital signs.
- Trial name
- FREJYA/IBV (NCT05947721)
- Where
- Spain
- Volunteers
- 60 people, healthy volunteers welcome
- Sponsor
- Instituto de Biomecanica de Valencia
PEEP, Occult
Evaluation of AI Models in Determining the Optimal PEEP
his study is designed as a prospective observational clinical trial. Patients over 18 years old who are hemodynamically stable and require mechanical ventilation in the Intensive Care Unit (ICU) will be included.
- Trial name
- NCT06844916
- Testing
- AI-Assisted PEEP Optimization
- Where
- Turkey (Türkiye)
- Volunteers
- 145 people
- Sponsor
- Kanuni Sultan Suleyman Training and Research Hospital
Lung Nodule
AI-based Low Dose CBCT Reconstruction for Clinical Application
The goal of this clinical trial is to learn if AI-based low dose CBCT reconstructed images can guide lung puncture effectively. The main questions it aims to answer are: 1.
- Trial name
- NCT06831617
- Testing
- AI-based low dose CBCT reconstructed images system, Conventional CBCT images system
- Where
- 3 sites in China
- Volunteers
- 400 people
- Sponsor
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Lung Diseases
AI in PRImary Care Spirometry Pathways for Diagnosis of Lung Disease (APRIL)
To investigate the feasibility of performing a future real-world randomised controlled trial to determine the clinical effectiveness of ArtiQ.Spiro in supporting diagnostic performance of primary care staff in the interpretation…
- Trial name
- APRIL (NCT05865249)
- Testing
- Spirometry decision support software (ArtiQ.Spiro)
- Where
- 2 sites in United Kingdom
- Volunteers
- 63 people
- Sponsor
- Royal Brompton & Harefield NHS Foundation Trust
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.
Gastric Intestinal Metaplasia
Efficacy of an AI System in Training Endoscopists to Assess Gastric Intestinal Metaplasia Via the EGGIM Score
This prospective randomized controlled trial with a crossover design incorporated image-enhanced endoscopy (IEE) videos demonstrating complete standardized examinations of five standard gastric areas (antrum greater curvature…
- Trial name
- NCT07208864
- Testing
- AI-assisted EGGIM scoring, Conventional EGGIM scoring
- Where
- China
- Volunteers
- 8 people
- Sponsor
- Qilu Hospital of Shandong University
Cardiovascular-kidney-metabolic Syndrome
AI Chatbot-Enabled ePRO Monitoring and Nurse-Led Self-Management for Early-Stage Cardiovascular-Kidney-Metabolic Syndrome
This randomized controlled trial will evaluate the effectiveness of an AI chatbot-enabled electronic patient-reported outcome (ePRO) monitoring and nurse-led self-management intervention for adults with early-stage…
- Trial name
- NCT07577284
- Testing
- AI chatbot-enabled nurse-led program., Usual Care
- Where
- Taiwan
- Volunteers
- 80 people
- Sponsor
- Taipei Medical University
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