Clinical trials: Machine Learning
Cancer
Implementation of a Tool to Identify Social Weaknesses in the Cancer Care Pathway
Social inequalities in the face of cancer are significant in all countries. They are characterized by higher mortality among people may be in the lower socioeconomic category.
- Trial name
- iDEFCO (NCT04015895)
- Testing
- DEFCO tool
- Where
- 8 sites in France
- Volunteers
- 437 people
- Sponsor
- Centre Hospitalier Universitaire de Saint Etienne
Kidney Calculi
Apply Machine Learning to the Interpretation of Urinary Crystal Morphology.
The goal of this observational study is to developing an image-based artificial intelligence software that can automatically interpret the types and sizes of crystals in urine.
- Trial name
- NCT06178575
- Volunteers
- 200 people
- Sponsor
- Yi-Shiou Tseng
Opioid Use Disorder
Mobile Peer Support for OUD Recovery
The COVID-19 pandemic puts individuals recovering from opioid use disorders (OUDs), an already vulnerable population, at increased risk of overdose due to decreased access to treatment, decreased social support, and increased…
- Trial name
- MPS (NCT05405712)
- Testing
- Mobile Phone App
- Where
- 2 sites in United States
- Volunteers
- 1,300 people
- Sponsor
- Brown University
Pediatric ALL, Sepsis
Evaluation of Pediatric eCART Implementation
This is a study comparing 3 years of retrospective data (pre-implementation) to 2 years of prospective data after the implementation of a pediatric version of Electronic Cardiac Arrest Risk Triage (pediatric eCART), a clinical…
- Trial name
- NCT06771830
- Testing
- Pediatric eCART
- Where
- United States
- Volunteers
- 30,000 people
- Sponsor
- University of Wisconsin, Madison
Postoperative Pulmonary Complications
PrEventing PostoPERative Pulmonary Complications by Establishing a MachINe-learning assisTed Approach
Postoperative pulmonary complications (POPC) are common after general anaesthesia and are a major cause of increased morbidity and mortality in surgical patients.
- Trial name
- PEPPERMINT (NCT05789953)
- Where
- Germany
- Volunteers
- 512 people
- Sponsor
- Britta Trautwein
Murmur, Heart, Innocent Murmurs
Real-World Evaluation of Eko Algorithms in a Point of Care Setting
The purpose of this research is to prospectively test and validate the utility of Eko artificial intelligence (AI) plus Eko Murmur Analysis Software (EMAS) murmur characterization in algorithm in a real world, point-of-care…
- Conditions
- Murmur, Heart, Innocent Murmurs, Heart Murmurs, Pathologic Murmur
- Trial name
- NCT05459545
- Testing
- Use of Eko CORE and Eko CORE 500 electronic stethoscope
- Where
- 5 sites in United States
- Volunteers
- 371 people, healthy volunteers welcome
- Sponsor
- Eko Devices, Inc.
Surgery
AI-driven Clinical Decision Support for Perioperative Blood Orders
20 million patients have surgery in the United States every year, with approximately 1 million of those patients requiring life-saving blood transfusion.
- Trial name
- SPATH (NCT07223853)
- Testing
- S-PATH clinical decision support system, Usual care
- Where
- United States
- Volunteers
- 50 people
- Sponsor
- Washington University School of Medicine
Mechanical Ventilation Pressure High, Ventilator-Associated Pneumonia (VAP)
Dynamic Airway Resistance & ML: Guide Sputum Suction in Ventilated Patients
Research has shown that timely suctioning not only improves survival rates but also enhances the quality of life in ventilator-dependent patients.
- Conditions
- Mechanical Ventilation Pressure High, Ventilator-Associated Pneumonia (VAP), Respiratory Depression Neonatal
- Trial name
- NCT07375667
- Testing
- The dynamics of airway resistance, conventional suctioning
- Where
- 3 sites in China
- Volunteers
- 258 people
- Sponsor
- Affiliated Hospital of Nantong University
Neck Pain, Disability Physical
ML for Neck Disability Using Muscle and Joint
conduct machine learning models to identify different aspects that can give us an impression about the disability in patients with neck pain. By using 17 different classifier and regressor models.
- Trial name
- NCT05291377
- Where
- Egypt
- Volunteers
- 90 people
- Sponsor
- Kafrelsheikh University
Acute Kidney Injury
Prospective Validation of AKI Prediction
The purpose of this prospective observational study is to implement, deploy, and quantify accuracy of an existing Pediatric Early AKI Risk Score algorithm.
- Trial name
- NCT06804200
- Where
- United States
- Volunteers
- 800 people
- Sponsor
- Adam C Dziorny
Gastric Cancers
Prediction of Postoperative Complications and Survival in Gastric Cancer Using Preoperative Blood Markers
Gastric cancer is one of the most common cancers worldwide, especially in East Asia. Although surgery remains the main treatment, patients may experience postoperative complications and have varying long-term survival outcomes.
- Trial name
- NCT06686966
- Testing
- gastric cancer
- Volunteers
- 3,400 people
- Sponsor
- First Affiliated Hospital of Chongqing Medical University
Artificial Intelligence, Machine Learning
Appropriate Use of Blood Cultures in the Emergency Department Through Machine Learning
The goal of this clinical trial is to study whether the use of our blood culture prediction tool is non-inferior to current practice and if it can improve certain outcomes in all adult patients presenting to the emergency…
- Conditions
- Artificial Intelligence, Machine Learning, Microbiology, Emergency Service, Hospital
- Trial name
- ABC (NCT06163781)
- Testing
- Blood culture prediction tool
- Where
- Netherlands
- Volunteers
- 7,584 people, healthy volunteers welcome
- Sponsor
- Amsterdam UMC, location VUmc
Stroke, Ischemic, Stroke Hemorrhagic
Study on the Performance of a Machine Learning Algorithm Recognizing and Triaging Large Vessel Occlusions Using Non-contrast CT Scans
The goal of this prospective observational study is to assess the effectiveness and performance of Methinks AI stroke imaging software platform in acute Code Stroke patients, and as a comparator to study sites utilizing existing…
- Conditions
- Stroke, Ischemic, Stroke Hemorrhagic, Stroke, Acute, Brain Ischemia
- Trial name
- SMART-LVO (NCT06216457)
- Testing
- AI software for Stroke
- Volunteers
- 5,000 people
- Sponsor
- Methinks Software SL
Spinal Muscular Atrophy
MAP THE SMA: a Machine-learning Based Algorithm to Predict THErapeutic Response in Spinal Muscular Atrophy
Spinal Muscular Atrophy (SMA) is caused by the homozygous loss of the Survival Motor Neuron (SMN) 1 gene, which leads to degeneration of spinal alpha-motor neurons and muscle atrophy.
- Trial name
- MAP_THE_SMA-01 (NCT05769465)
- Testing
- disease modifying treatments
- Where
- Italy
- Volunteers
- 247 people
- Sponsor
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Pleural Diseases, Lung Cancer
Developing a Machine Learning Model to Predict Pleural Adhesion Preoperatively Using Pleural Ultrasound
This study aims to investigate the accuracy of using pleural ultrasound (USP) to identify pleural adhesions in patients who plan to receive video-assisted thoracoscopic surgery.
- Conditions
- Pleural Diseases, Lung Cancer, Machine Learning
- Trial name
- NCT06423066
- Testing
- Pleural ultrasound
- Where
- China
- Volunteers
- 200 people
- Sponsor
- Peking Union Medical College Hospital
Rectum Cancer
Machine Learning-based Surgical Guidance System for Robot-assisted Rectal Surgery
The aim of the study is to evaluate the technical feasibility and applicability of a surgical assistance system based on image recognition algorithms in a first-in-human pilot study.
- Trial name
- CoBot2 (NCT05652361)
- Testing
- Additional visualisation of surgical assistance during surgery
- Where
- Germany
- Volunteers
- 12 people
- Sponsor
- Technische Universität Dresden
Attention Deficit-hyperactivity Disorder
Assesment of TDApp1 an eHelath Tool to Make Therapeutic Recommendations for Patients With ADHD
This is a 3-week open label, one group study to determine the agreement between the pharmacological treatment recommended by TDApp1 and the interventions recommended by relevant clinical practice guidelines.
- Trial name
- NCT04228094
- Testing
- TDApp1: an eHealth intervention
- Where
- Spain
- Volunteers
- 33 people
- Sponsor
- Universitat de Girona
Heart Failure
Improving Risk Stratification of Emergency Department Patients With Acute Heart Failure
The primary goal is to build and test a previously developed and validated risk model and clinical decision support tool embedded within the electronic health record to improve risk stratification of emergency department (ED)…
- Trial name
- NCT06065761
- Testing
- Comprehensive ED heart failure management tool
- Where
- 21 sites in United States
- Volunteers
- 17,459 people
- Sponsor
- Kaiser Permanente
Physical Inactivity
The Effect of a Machine Learning-Based Mobile Application on Physical Activity in Overweight and Obese Women
The goal of this clinical trial is to evaluate the effect of an algorithm-driven mobile application that provides personalized recommendations for increasing physical activity, which is an important health behavior, in the…
- Trial name
- NCT06225518
- Testing
- Individualized physical activity management system
- Where
- Turkey (Türkiye)
- Volunteers
- 80 people, healthy volunteers welcome
- Sponsor
- Istanbul University - Cerrahpasa
Sepsis
Early Prediction of Sepsis
In this clinical trial a novel Medical Device Software will be validated prospectively. The software incorporates a machine learning algorithm capable of predicting sepsis by using routine clinical variables in adult patients at…
- Trial name
- ExPRESS (NCT04570618)
- Testing
- Unblinded AlgoDx Sepsis Prediction Algorithm, Blinded AlgoDx Sepsis Prediction Algorithm
- Where
- Sweden
- Volunteers
- 320 people
- Sponsor
- AlgoDx