Clinical trials: Machine Learning, active
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
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
Breast Neoplasms
Predicting Long-Term Clinical Outcomes in Chinese Breast Cancer Patients Receiving Neoadjuvant Chemotherapy
At present, the majority of studies on neoadjuvant chemotherapy (NAC) in patients with breast cancer (BC) use pathological complete response (pCR) as a surrogate marker for patient prognosis, with significant improvements in pCR…
- Trial name
- NCT06856616
- Where
- China
- Volunteers
- 6,000 people
- Sponsor
- The Third Affiliated Hospital of Harbin Medical University
Colonoscopy
External, Multicentre Validation of a Machine-Learning Model to Predict Colonic Adenoma in Indian Adults
Colorectal adenomas are precursors to colorectal cancer (CRC). Accurate pre-procedure risk stratification could optimize colonoscopy yield and resource allocation in India, where adenoma prevalence varies by age, sex, and…
- Trial name
- NCT07329816
- Testing
- Not Applicable / Observational study
- Volunteers
- 1,000 people
- Sponsor
- Asian Institute of Gastroenterology, India
Branch Atheromatous Disease, Acute Ischemic Stroke
Early Identification and Diagnosis of BAD-related Stroke
Branch atheromatous disease (BAD)-related stroke is an important subtype of acute ischemic stroke involving penetrating arteries and is associated with early neurological deterioration.
- Conditions
- Branch Atheromatous Disease, Acute Ischemic Stroke, Cerebral Infarction
- Trial name
- SMART-BAD (NCT07693816)
- Testing
- Multisource clinical-imaging artificial intelligence diagnostic assessment
- Where
- 11 sites in China
- Volunteers
- 1,602 people
- Sponsor
- Peking Union Medical College Hospital
Labour Analgesia
Prediction of Local Anaesthetic Dosing During Labour Epidural Analgesia
Epidural analgesia is the gold standard for controlling labour pain. However, labour pain happens during neuraxial analgesia, due to anaesthetic, obstetric, maternal factors.
- Trial name
- DIANA (NCT07614516)
- Testing
- Machine-learning prediction model
- Where
- Italy
- Volunteers
- 12,500 people
- Sponsor
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Renal Clear Cell Carcinoma, HIF-2α
Predicting HIF-2α Levels in Clear Cell Kidney Cancer Using Machine Learning
This project aims to conduct a multicenter retrospective study to collect clinical, CT imaging, and pathological data from patients.
- Conditions
- Renal Clear Cell Carcinoma, HIF-2α, Radiomics, Nomogram
- Trial name
- NCT07332923
- Where
- China
- Volunteers
- 500 people
- Sponsor
- First Affiliated Hospital of Fujian Medical University
EGPA - Eosinophilic Granulomatosis With Polyangiitis, HES - Hypereosinophilic Syndrome
The Use of Machine Learning Techniques for the Differential Diagnosis Between Eosinophilic Granulomatosis With Polyangiitis and Hypereosinophilic Syndrome
The purpose of this study is to collect clinical, laboratory, and instrumental data from patients with eosinophilic granulomatosis with polyangiitis or hypereosinophilic syndrome, which will then be analyzed using artificial…
- Trial name
- NCT07275190
- Testing
- Blood draw for the laboratory assessment
- Where
- Italy
- Volunteers
- 60 people
- Sponsor
- Fondazione IRCCS Policlinico San Matteo di Pavia
Healthy, Foot
Implementation of Machine Learning Into Optical Pedography
This study aims to evaluate the validity and reliability of a proposed plantar pressure assessment intrument based on an implementation of machine learning into optical pedography.
- Conditions
- Healthy, Foot, Pressure Area, Pressure Distribution
- Trial name
- NCT07451509
- Testing
- Optical pedography
- Where
- Czechia
- Volunteers
- 150 people, healthy volunteers welcome
- Sponsor
- Palacky University
Apnea, Sleep Disorders
A Study to Learn About the Monthly Dosing Study Medicine Called Berobenatide in Adults With Breathing Problems During Sleep and Overweight or Obesity Who Use a Breathing Machine (PAP) (VESPER-OSA 1)
This study is being done to learn about the safety and effects of a study medicine called berobenatide (bear-oh-BEN-uh-tide). The study will see if berobenatide can help adults with breathing problems during sleep (obstructive…
- Conditions
- Apnea, Sleep Disorders, Overweight and/or Obesity
- Trial name
- NCT07823608
- Testing
- Berobenatide
- Where
- 6 sites in United States
- Volunteers
- 258 people
- Sponsor
- Pfizer
Tinnitus
Application of Machine Learning Based on fNIRS in Predicting Acupuncture's Efficacy in Treating Tinnitus
This trial aims to use machine learning to analyze fNIRS imaging data of specific brain regions of tinnitus patients, thereby constructing a predictive model of the clinical efficacy of acupuncture for SNT.
- Trial name
- NCT06364670
- Testing
- acupuncture
- Where
- China
- Volunteers
- 500 people
- Sponsor
- The Third Affiliated hospital of Zhejiang Chinese Medical University
Osteogenesis Imperfecta, Rare Bone Disorders
Morphology in Oral Rare Syndromes & Artificial Intelligence for Clinical Diagnosis
MOSAIC aims to determine whether oro-dental morphological anomalies, particularly palatal morphology, associated with rare bone and cartilage diseases can be precisely characterized using 3D digital models analysed through…
- Conditions
- Osteogenesis Imperfecta, Rare Bone Disorders, Hypophosphatemia, X-Linked
- Trial name
- MOSAIC (NCT07666269)
- Testing
- intra-oral 3D optical impression
- Where
- France
- Volunteers
- 240 people, healthy volunteers welcome
- Sponsor
- University Hospital, Bordeaux
Glioma
MR Based Survival Prediction of Glioma Patients Using Artificial Intelligence
This registry aims to collect clinical, molecular and radiologic data including detailed survival data, clinical parameters, molecular pathology (1p/19q codeletion, MGMT methylation, IDH and TERTp mutations, etc) and…
- Trial name
- NCT04215211
- Testing
- Survival prediction for glioma patients
- Where
- China
- Volunteers
- 2,500 people
- Sponsor
- The First Affiliated Hospital of Zhengzhou University
Deep Vein Thrombosis
Systematic Machine Learning Algorithm for Rapid Thrombosis Detection
The goal of this clinical trial is to compare the use of a machine learning-based algorithm and point-of-care D-dimer to laboratory D-dimer and compression ultrasound to exclude deep vein thrombosis in the under extremities in…
- Trial name
- DVT-SMART (NCT06842446)
- Testing
- POC D-dimer, POC ultrasound, Machine learning model
- Where
- Norway
- Volunteers
- 1,000 people
- Sponsor
- Ostfold Hospital Trust
Infection, Bloodstream
BACTERIUM: Study for a Machine-learning-based Model to Predict Bloodstream Infections
An increase of healthcare-associated infections caused by multidrug- resistant organisms (MRDO) is currently observed. One of the main causes of the emergence of a MDRO infection is an overuse of antibiotics.
- Trial name
- BACTERIUM (NCT05876598)
- Testing
- antibiotic treatments
- Where
- Italy
- Volunteers
- 5,000 people
- Sponsor
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS
PTSD - Post Traumatic Stress Disorder, Trauma-related Nightmares
Validation of an Algorithm for Predicting Awakenings Associated With Trauma-related Nightmares, Based on the Analysis of Physiological Patterns in Military and Former Military Patients Suffering From Post-traumatic Stress Disorder
The goal of this clinical trial is to validate an artificial intelligence algorithm called CAUD-PIN (CAUchemar Detection on INdividualized Parameters) to predict nightmare-related awakenings in military personnel and veterans…
- Trial name
- CAUD-PIN (NCT07851480)
- Testing
- CAUD-PIN (CAUchemar Detection on INdividualized Parameters) - AI-based predictive algorithm forTrauma-related nightmare awakenings
- Where
- 3 sites in France
- Volunteers
- 27 people
- Sponsor
- Direction Centrale du Service de Santé des Armées
Cardiotoxicity, DPP3
Cardiovascular Complications in Patients Undergoing Allogeneic Hematopoietic Stem Cell Transplantation.
Allogeneic hematopoietic stem cell transplantation (HSCT) represents a major therapeutic strategy for malignant hematologic diseases, with the number of procedures steadily increasing in France each year.
- Conditions
- Cardiotoxicity, DPP3, HSCT, Allogeneic Hematopoietic Stem Cell Transplantation
- Trial name
- ALLOCARDIOTOX (NCT07157670)
- Where
- France
- Volunteers
- 400 people
- Sponsor
- Assistance Publique - Hôpitaux de Paris
Ischemic Stroke, Hemorrhagic Stroke
Using Machine Learning and Biomarkers for Early Detection of Delayed Cerebral Ischemia
The overall goal of this project is to determine if machine learning and analysis of neurospecific biomarkers can enable early detection of upcoming or ongoing cerebral ischaemia in patients suffering from subarachnoid…
- Trial name
- CIDAIBASSAH (NCT06069973)
- Testing
- No intervention, observational study
- Where
- Sweden
- Volunteers
- 1,500 people
- Sponsor
- Sahlgrenska University Hospital
Refractive Errors, Cycloplegic Refraction
ML Models Predicting Cycloplegic Refractive Error Based on Non-Cycloplegic Parameters in Myopic Adults
This study presents a machine learning model that predicts cycloplegic refraction in adults with myopia using standard non-cycloplegic eye measurements, aiming to reduce the need for cycloplegic drops while still identifying…
- Conditions
- Refractive Errors, Cycloplegic Refraction, Accommodation
- Trial name
- NCT07690813
- Testing
- Machine learning model for predicting cycloplegic refraction
- Where
- China
- Volunteers
- 2,500 people
- Sponsor
- Second Affiliated Hospital of Nanchang University
Patient Safety
Machine Learning Prediction of Parameters of Early Warning Scores in Intensive Care Units
A large number of different organ functions are recorded in real time for patients being monitored in an intensive care unit. On the one hand, the measured values collected are used for continuous monitoring of vital parameters…
- Trial name
- AIM-PEW-ICU (NCT06259812)
- Testing
- Parameters of Early Warning Scores
- Where
- Austria
- Volunteers
- 8,000 people, healthy volunteers welcome
- Sponsor
- Kepler University Hospital