Clinical trials: Machine Learning
Prostate Cancer
The PROSECCA Study, Answering New Questions in Prostate Cancer
Nearly half of all cancer patients receive radiotherapy as part of their treatment and although it is effective at destroying cancerous lesions deep within the body, this comes at the cost of damaging healthy, or normal, tissues.
- Trial name
- PROSECCA (NCT06714630)
- Where
- United Kingdom
- Volunteers
- 15,000 people
- Sponsor
- University of Edinburgh
Injury Traumatic, Injuries
Trauma Follow-Up Prediction (Project 2: Aim 2)
Approximately 9% of the world's deaths, more than 5 million deaths annually, are due to injury. In high-income countries, where the epidemiology and outcomes of traumatic injury are well characterized, trauma primarily affects…
- Trial name
- NCT05464017
- Testing
- Optimized version of the mHealth screening tool (intervention) using the machine learning approach
- Volunteers
- 852 people, healthy volunteers welcome
- Sponsor
- University of Buea
Vital Signs
A Machine Learning Approach to Continuous Vital Sign Data Analysis
Study hypothesis: Machine Learning algorithms and techniques previously developed for use in the robotics field can be applied to the field of medicine.
- Trial name
- NCT01448161
- Volunteers
- 605 people
- Sponsor
- University of Colorado, Denver
Attention Deficit Hyperactivity Disorder
Αn Information System for Symptom Diagnosis and Improvement of Attention Deficit Hyperactivity Disorder (ADHD360)
ADHD360 will be an innovative integrated platform for early ADHD diagnosis and intervention against its symptoms. In the core of the platform design there will be a serious game along with a mobile application to monitor behavior…
- Trial name
- ADHD360 (NCT04362982)
- Testing
- ADHD360 platform: An intervention intergrating a serious game along with a mobile application for daily behavioral monitoring.
- Where
- Greece
- Volunteers
- 43 people, healthy volunteers welcome
- Sponsor
- Aristotle University Of Thessaloniki
Bipolar Disorder Depression, Major Depression
AI-based Multi-center Research on Identification/Classification/Aided Diagnosis of Mood Disorder
At present, diagnosis and recognition of depression and bipolar disorder are mainly based on subjective evidence such as clinical interview and scale evaluation.
- Trial name
- NCT05608135
- Where
- China
- Volunteers
- 960 people, healthy volunteers welcome
- Sponsor
- First Affiliated Hospital of Zhejiang University
Ovarian Cyst
Assessment of Ovarian Cysts Using Machine Learning
The study aims at creating a prediction model using machine learning algorithms that is capable of predicting malignant potential of ovarian cysts/masses based on patient characteristics, sonographic findings, and biochemical…
- Trial name
- OCID (NCT05342298)
- Testing
- prediction model
- Where
- 2 sites in Egypt
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- Assiut University
Glioma
Histopathology Images Based Prediction of Molecular Pathology in Glioma Using Artificial Intelligence
This registry aims to collect clinical, molecular and radiologic data including detailed clinical parameters, molecular pathology (1p/19q co-deletion, MGMT methylation, IDH and TERTp mutations, etc) and images of HE slices in…
- Trial name
- NCT04217044
- Testing
- Histopathology images based prediction of molecular pathology
- Where
- China
- Volunteers
- 3,000 people, healthy volunteers welcome
- Sponsor
- The First Affiliated Hospital of Zhengzhou University
Kawasaki Disease
Kawasaki MATCH Trial
Evaluating the impact of a machine-learning clinical decision support tool on provider practice when evaluating febrile patients with Kawasaki Disease (KD) and non-KD illnesses.
- Trial name
- MATCH (NCT07291245)
- Testing
- Kawasaki MATCH
- Where
- United States
- Volunteers
- 200 people
- Sponsor
- University of California, San Diego
Attention Deficit Hyperactivity Disorder
Community-Based Care for Minority Adolescents With ADHD: Improving Fidelity With Machine Learning-Assisted Supervision and Fidelity Feedback.
This project proposes to reduce disparities in care among disadvantaged racial/ethnic minority adolescents with ADHD by improving community therapist fidelity to evidence-based behavior therapy through a technology-assisted…
- Trial name
- NCT05135065
- Testing
- Artificial Intelligence-Assisted Supervision Protocol
- Where
- United States
- Volunteers
- 51 people
- Sponsor
- Seattle Children's Hospital
Chemotherapy Induced Nausea and Vomiting, Quality of Life (QOL)
Vomiting Prevention in Children With Cancer
The goal of this single arm trial is to learn if a machine learning (ML) model predicting the risk of vomiting within the next 96 hours will impact vomiting outcomes in inpatient cancer pediatric patients.
- Conditions
- Chemotherapy Induced Nausea and Vomiting, Quality of Life (QOL), Pediatric Cancer
- Trial name
- NCT06886451
- Testing
- ML-based intervention
- Where
- Canada
- Volunteers
- 1,953 people
- Sponsor
- The Hospital for Sick Children
Genetic Disease, Neurogenetic Disorders
Pediatric Neurogenetic Diagnosis Support Platform
This study evaluates a diagnostic support platform, DIAGEN-IA, designed to identify pediatric neurological diseases with a genetic basis.
- Trial name
- DIAGEN-IA (NCT06725901)
- Testing
- Web-Based Application
- Where
- Chile
- Volunteers
- 9 people, healthy volunteers welcome
- Sponsor
- Universidad Nacional Andres Bello
Drug-induced Liver Injury, Autoimmune Hepatitis
Discrimination of DILI and AIH by Artificial Intelligence
A retrospective, multi-center, non-interventional cohort study has been going to explore whether artificial intelligence can discriminate Drug-induced liver injury and Autoimmune hepatitis.
- Trial name
- NCT05532345
- Where
- China
- Volunteers
- 2,583 people
- Sponsor
- Beijing Friendship Hospital
Appendectomy, Appendicitis
Early Detection of Infection Using the Fitbit in Pediatric Surgical Patients
The purpose of this study is to analyze Fitbit data to predict infection after surgery for complicated appendicitis and the effect this prediction has on clinician decision making.
- Conditions
- Appendectomy, Appendicitis, Appendicitis Acute
- Trial name
- i-DETECT (NCT06395636)
- Testing
- Infection-Prediction Algorithm
- Where
- 4 sites in United States
- Volunteers
- 500 people
- Sponsor
- Ann & Robert H Lurie Children's Hospital of Chicago
Neonatal Intensive Care Unit, Medication Errors
Drug-Related Problems in Neonatal Patients
Drug-related problems in newborn babies have been reported with a rate of 4-30%. It is estimated that the higher rates of these problems in hospitalized children under the age of two are related to the variety of drugs used and…
- Conditions
- Neonatal Intensive Care Unit, Medication Errors, Drug-Related Problems, Adverse Drug Event
- Trial name
- NCT04899960
- Testing
- Clinical Pharmacist Intervention
- Where
- Turkey (Türkiye)
- Volunteers
- 512 people
- Sponsor
- Hacettepe University
Dental Anxiety in Children
AI-Assisted Evaluation of Dental Anxiety in Children: A Machine Learning Approach
This observational study evaluated whether children's dental anxiety could be identified from their speech using artificial intelligence and machine learning methods.
- Trial name
- NCT07797777
- Testing
- Multimodal Speech-Based Dental Anxiety Assessment
- Where
- Turkey (Türkiye)
- Volunteers
- 262 people, healthy volunteers welcome
- Sponsor
- Marmara University
Neuroblastoma (NB), Prognosis
Risk Model for Metastasis Detection of Neuroblastoma
Neuroblastoma (NB) is the most common extracranial solid tumor in children, accounting for about 15% of tumor-related mortality.
- Conditions
- Neuroblastoma (NB), Prognosis, Bone Marrow Metastasis, Bone Metastases
- Trial name
- NB (NCT06703944)
- Testing
- risk model in diagnosis and prognosis
- Where
- 3 sites in China
- Volunteers
- 500 people
- Sponsor
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Hypospadias
Identification of Hypospadias Parameters Using Digital Photography and Artificial Intelligence
The goal of this observational study is to develop and validate a digital pattern recognition system based on artificial neural network to determine various parameters in hypospadias.
- Trial name
- ASHOKA (NCT05569863)
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- Universitas Indonesia
Delayed Extubation, Postoperative Intensive Care
Factors Associated With Late Extubation in Postoperative Patients in the Surgical Intensive Care Unit
Timely removal of a breathing tube after surgery is an important part of recovery for patients admitted to the intensive care unit (ICU).
- Conditions
- Delayed Extubation, Postoperative Intensive Care, Mechanical Ventilation Weaning
- Trial name
- NCT07658456
- Testing
- No Intervention - Retrospective Observational Study
- Where
- Taiwan
- Volunteers
- 204 people
- Sponsor
- Kaohsiung Armed Forces General Hospital
Gastric Neuroendocrine Carcinoma (G-NEC), Postoperative Adjuvant Therapy for G-NEC
ML Decision Model for G-NEC Adjuvant Therapy
Gastric neuroendocrine carcinoma (G-NEC) is a rare and aggressive tumor originating from neuroendocrine cells in the stomach lining. It is characterized by a high propensity for recurrence and a generally poor prognosis.
- Conditions
- Gastric Neuroendocrine Carcinoma (G-NEC), Postoperative Adjuvant Therapy for G-NEC, Survival Outcomes, Machine Learning
- Trial name
- G-NEC (NCT06663852)
- Where
- China
- Volunteers
- 1,505 people
- Sponsor
- Chang-Ming Huang, Prof.
COVID-19 Infection
Clinical Characteristics and Prognostic Factors of Patients With COVID-19 (Coronavirus Disease 2019)
This is a multicenter, non-interventional, retrospective study using data captured in the EHRs (Electronic Health Records) of the participating hospital sites to determine factors that predict disease prognosis and outcomes in…
- Trial name
- NCT04569851
- Where
- 2 sites in Spain
- Volunteers
- 100,000 people
- Sponsor
- Savana Research