Clinical trials: Machine Learning
Bedwetting, Nocturnal Enuresis
Randomized Study Of Novel Enuresis Alarm vs Standard Bedwetting Alarm
Identify the dry night rate in patients using the GoGoband® nocturnal enuresis device vs a standard Pflaundler bedwetting alarm.
- Conditions
- Bedwetting, Nocturnal Enuresis, Urinary Incontinence
- Trial name
- NCT05214131
- Testing
- gogoband, SNEA group
- Where
- United States
- Volunteers
- 16 people, healthy volunteers welcome
- Sponsor
- Yale University
Scoliosis Idiopathic Adolescent, Scoliosis
Deep Learning for Early Scoliosis Detection Using mmWave Radar Gait Data
Scoliosis is a sideways curvature of the spine that often develops during childhood and adolescence. When detected early, scoliosis can be managed effectively with non-invasive approaches such as bracing and physiotherapy, while…
- Trial name
- ScoliRadar-AI (NCT07593560)
- Testing
- mmWave Radar Gait Assessment
- Where
- Turkey (Türkiye)
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- Gebze Technical University
Congenital Anomalies, Neonatal Complications
AI-Powered Neonatal Risk Assessment for Improved Perinatal Outcomes
This study aims to develop advanced artificial intelligence (AI) models that predict neonatal risks and complications based on historical multimodal health data, including ultrasound and MRI scans.
- Conditions
- Congenital Anomalies, Neonatal Complications, Perinatal Outcomes, Perinatal Outcomes of the Mother and Fetus
- Trial name
- NCT07064356
- Volunteers
- 50,000 people, healthy volunteers welcome
- Sponsor
- FetalFirst Limited
Sepsis
A Machine Learning Predictive Model for Sepsis
Timely and accurately predicting the occurrence of sepsis and actively intervening in treatment may effectively improve the survival and cure rate of patients with sepsis.
- Trial name
- NCT04771429
- Where
- China
- Volunteers
- 4,500 people, healthy volunteers welcome
- Sponsor
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Atherosclerosis, Wounds and Injuries
Machine Learning for Handheld Vascular Studies
The use of handheld arterial 'stethoscopes' (continuous wave Doppler devices) are ubiquitous in clinical practice. However, most users have received no formal training in their use or the interpretation of the returned data.
- Trial name
- DopplerZAM (NCT02932176)
- Testing
- Non-invasive vascular testing, machine-learning algorithm
- Where
- United States
- Volunteers
- 155 people, healthy volunteers welcome
- Sponsor
- Duke University
Spinal Muscular Atrophy Type 3, Duchenne Muscular Dystrophy
Wearable Technology to Assess Gait Function in SMA and DMD
The purpose of this project is to devise instrumented insoles capable of accurately measuring gait at each footfall, over multiple hours in any environment.
- Trial name
- NCT04193085
- Testing
- Observational
- Where
- United States
- Volunteers
- 39 people, healthy volunteers welcome
- Sponsor
- Columbia University
Preterm Birth Complication
Prediction of Adverse Outcome Using Fetal MRI in Pregnancies at Risk of Preterm Birth
1.4% of babies have a very premature birth (PTB) (less than 32 weeks of pregnancy). This can result in severe life-long complications including cerebral palsy, learning and behavioural difficulties and breathing problems.
- Trial name
- NCT05164432
- Testing
- MRI scan
- Where
- United Kingdom
- Volunteers
- 175 people, healthy volunteers welcome
- Sponsor
- King's College London
Adolescent Idiopathic Scoliosis (AIS)
Detection of Scoliosis
This study aims to evaluate whether plantar pressure data collected during standing and walking can be used with machine learning to support early detection of scoliosis in young people.
- Trial name
- NCT07581015
- Volunteers
- 500 people, healthy volunteers welcome
- Sponsor
- University College, London
Neonatal Encephalopathy, Hypoxic-Ischemic Encephalopathy
Neonatal Neurological Observation With Video AI
NeoNOVA is a multi-site, prospective, single-arm, silent observational study to determine: among (Population) infants admitted to newborn services during their inpatient hospital stay, whether (Intervention) continuous bedside…
- Conditions
- Neonatal Encephalopathy, Hypoxic-Ischemic Encephalopathy, Sedation, Sleep
- Trial name
- NeoNOVA (NCT07628829)
- Testing
- Continuous bedside video monitoring with AI anatomic landmark tracking for neurologic monitoring
- Where
- 2 sites in United States
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- Artemis AI Labs
Autism, Autism Spectrum Disorder
Online Evaluation of the Diagnostic Accuracy of BlinkLab's Digital Assessments for Autism
This observational study aims to evaluate how patterns of behavioral and sensorimotor responses measured using the BlinkLab Dx1 smartphone application relate to autism diagnoses in children ages 2 to 11.
- Conditions
- Autism, Autism Spectrum Disorder, Autism Spectrum Disorder (ASD), Neurodevelopmental Conditions
- Trial name
- NCT07590973
- Testing
- BlinkLab Dx1, Retrospective Neurodevelopmental Diagnostic Assessment
- Where
- United States
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- Blinklab Limited
Asthma, COPD
Acoustic Waveform Respiratory Evaluation
The study will evaluate the feasibility of using smartphone speakers and microphones to evaluate the caliber of the airways, detect airway obstruction, aid in airway disease diagnosis, and identify disease exacerbations.
- Conditions
- Asthma, COPD, Cystic Fibrosis, Ciliary Motility Disorders
- Trial name
- AWARE (NCT06512064)
- Testing
- AWARE
- Where
- 2 sites in United States
- Volunteers
- 800 people, healthy volunteers welcome
- Sponsor
- Indiana University
Voiding Dysfunction, Voiding Disorders
Artificial Intelligence-Based Analysis of Uroflowmetry Patterns in Children: a Machine Learning Perspective
Uroflowmetry is the one of the most commonly used non-invasive test for evaluating children with lower urinary tract symptoms (LUTS).
- Conditions
- Voiding Dysfunction, Voiding Disorders, Machine Learning
- Trial name
- NCT06814847
- Where
- Turkey (Türkiye)
- Volunteers
- 500 people, healthy volunteers welcome
- Sponsor
- Marmara University
Pulmonary Fibrosis, Healthy
Pulmonary Fibrosis Lung Sounds Study
The goal of this observational study is to test whether it is possible to detect particular lung sounds that are unique to patients with the lung disease pulmonary fibrosis and whether any such sounds could be analysed using…
- Trial name
- NCT05771740
- Testing
- Stemoscope (bluetooth sound amplifier)
- Volunteers
- 100 people, healthy volunteers welcome
- Sponsor
- Royal Devon and Exeter NHS Foundation Trust
Sport Injury, Osteoarthritis, Knee
Biometric Recognition and Rehabilitation Assessment of Lower Extremity Sports Injury Based on Gait Touch Information
The current common clinical methods cannot truly reflect the biomechanical status of the knee joint. Based on the foot-knee coupling mechanism, the simple and practical dynamic gait touch information provided by the 3D force…
- Trial name
- NCT04462913
- Testing
- no intervention
- Where
- China
- Volunteers
- 550 people, healthy volunteers welcome
- Sponsor
- Peking University Third Hospital
Cardiac Disease, Auscultation of Heart
Digital diagnoSis of Cardiac sOUNd in peDiatric Patients [DI-SOUND Study]
Neonatal screening procedures for potentially life-threatening congenital cardiovascular diseases (i.e., duct-dependent systemic or pulmonary circulation), currently implemented at the national level, rely primarily on…
- Conditions
- Cardiac Disease, Auscultation of Heart, Machine Learning
- Trial name
- DI-SOUND (NCT07542509)
- Where
- 5 sites in Italy
- Volunteers
- 1,000 people, healthy volunteers welcome
- Sponsor
- IRCCS Azienda Ospedaliero-Universitaria di Bologna
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
Crisis Intervention, Suicide and Depression
Brief Online Help-seeking Barrier Reduction Intervention
Objective: Mental illness is a leading cause of disease burden; however, many barriers prevent people from seeking mental health services.
- Trial name
- NCT03633825
- Testing
- Brief help-seeking barrier reduction intervention
- Where
- United States
- Volunteers
- 39,450 people, healthy volunteers welcome
- Sponsor
- Harvard University
Down Syndrome
Digital Dysmorphology Project
In this study, the investigators propose a novel method to detect Down syndrome using photography for facial dysmorphology, a tool called computer-aided diagnosis (CAD).
- Trial name
- NCT02651493
- Testing
- photographs
- Where
- United States
- Volunteers
- 750 people, healthy volunteers welcome
- Sponsor
- Kevin Cleary
Diabetes Mellitus
Diabetes Screening and Monitoring Using Tongue Images and Self-reported Symptoms: a Machine Learning Approach
Study Background: Diabetes mellitus (DM) is a major non-communicable disease. Diagnosis and self-management of DM is important. Currently, detection of diabetes requires blood tests, which is costly and inconvenient, especially…
- Trial name
- NCT05819151
- Testing
- HbA1c Test
- Where
- 2 sites in Hong Kong
- Volunteers
- 4,000 people, healthy volunteers welcome
- Sponsor
- Hong Kong Baptist University
Endometriosis, Pelvic Pain
Machine Learning for Early Diagnosis of Endometriosis(MLEndo)
The project aims to create a large prospective data bank using the Lucy medical mobile application and collect and analyze patient profiles and structured clinical data with artificial intelligence.
- Conditions
- Endometriosis, Pelvic Pain, Infertility, Female
- Trial name
- MLEndo (NCT06147687)
- Testing
- Self reported data collection
- Where
- 2 sites in Hungary
- Volunteers
- 10,000 people, healthy volunteers welcome
- Sponsor
- Semmelweis University