Clinical trials: Learning Model, active
Machine Learning, Prediction Models
Timely Ordering of Pharmacogenetic Testing
The goal of this trial is to learn if a machine learning (ML) model can help optimize drug therapy in the pediatric population. The main question[s] it aims to answer are whether a machine learning model predicting receipt of a…
- Conditions
- Machine Learning, Prediction Models, Pediatrics, Precision Medicine
- Trial name
- NCT06902688
- Testing
- ML-based intervention
- Where
- Canada
- Volunteers
- 275 people
- Sponsor
- The Hospital for Sick Children
Triple -Negative Breast Cancertriple, Meta-Learning
Establishment of a Multi-omics Prediction Model for Early Triple-negative Breast Cancer Based on UPGRADE-TNBC Study
Based on the UPGRADE-TNBC study, a high-quality TNBC sample repository was established. By integrating multi-source data-including clinical information, radiomics, pathological images, and molecular sequencing-and innovatively…
- Conditions
- Triple -Negative Breast Cancertriple, Meta-Learning, Predictive Models, Multimodal
- Trial name
- NCT07773818
- Testing
- Collect data
- Where
- China
- Volunteers
- 32 people
- Sponsor
- Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Alpha-1-antitrypsin Deficiency, Emphysema
Development of a Prediction Score for the Occurrence of Death or Lung Transplantation in Patients With Emphysema Secondary to Alpha-1-anti-tripsin Deficiency
Emphysema linked to alpha-1-antitrypsin deficiency (DAAT): towards a better prediction of risks Emphysema caused by alpha-1-antitrypsin deficiency (DAAT) is a rare genetic disorder that can lead to serious complications, such as…
- Conditions
- Alpha-1-antitrypsin Deficiency, Emphysema, Artificial Intelligence (AI), Predictive Learning Models
- Trial name
- FLARE (NCT07715617)
- Where
- 4 sites in France
- Volunteers
- 230 people
- Sponsor
- University Hospital, Bordeaux
Artificial Intelligence (AI), Machine Learning
Development and Pre-validation of a Machine Learning-based Prediction Algorithm for Early Functional Recovery in Patients Undergoing Hip and Knee Replacement Surgery
The goal of this observational study is to develop and pre-validate a machine learning algorithm to predict early recovery of mobility in patients undergoing hip or knee joint replacement surgery.
- Conditions
- Artificial Intelligence (AI), Machine Learning, Joint Replacement, Predictive Model
- Trial name
- FISIO_IA (NCT07333560)
- Testing
- Predictive Model for Early Mobility Recovery and Length of Stay
- Where
- 2 sites in Italy
- Volunteers
- 943 people
- Sponsor
- Istituto Ortopedico Rizzoli
Endodontic Retreatment, Non-surgical Retreatment
Development and Validation of a Deep Learning Model to Predict Endodontic Retreatment Difficulty From Periapical Radiographs
The aim of this study is to develop and evaluate an artificial intelligence-based model capable of analyzing periapical radiographs of maxillary and mandibular molars to predict the difficulty level of non-surgical root canal…
- Conditions
- Endodontic Retreatment, Non-surgical Retreatment, Endodontics, AI (Artificial Intelligence)
- Trial name
- Ai Retreatment (NCT07611279)
- Testing
- Deep Learning Model to Predict Endodontic Retreatment Difficulty from Periapical Radiographs
- Volunteers
- 123 people
- Sponsor
- Cairo University
BIS, BIS-EEG
Deep Learning Framework for Continuous Depth of Anesthesia Forecasting
The integration of Artificial Intelligence (AI) in anesthesiology offers the potential to shift patient monitoring from reactive to predictive.
- Conditions
- BIS, BIS-EEG, Artifical Intelligence, Intraoperative
- Trial name
- NCT07536230
- Where
- Belgium
- Volunteers
- 115 people, healthy volunteers welcome
- Sponsor
- Universitair Ziekenhuis Brussel
Critical Illness, Enteral Nutrition Intolerance
Predictive Value of Gastrointestinal Blood Flow for Enteral Nutrition Intolerance in Critically Ill Patients
This study aims to explore the correlation between gastrointestinal blood flow and the incidence of enteral nutrition intolerance (ENI) and its symptoms in critically ill patients, construct and compare predictive models…
- Conditions
- Critical Illness, Enteral Nutrition Intolerance, Enteral Nutrition Feeding, Prediction Models
- Trial name
- NCT07521111
- Where
- China
- Volunteers
- 500 people
- Sponsor
- Ruijin Hospital
Delirium, Prediction Models
Research on the Development and Validation of an Early Prediction Model for Delirium
Delirium has a high incidence rate and significantly affects patient prognosis. Diagnosis often relies on manual assessment, which is subject to strong subjectivity, high rates of missed diagnosis, and poor stability.
- Conditions
- Delirium, Prediction Models, Machine Learning
- Trial name
- NCT07337356
- Volunteers
- 795 people
- Sponsor
- Ruijin Hospital
Spiritual Care, Flipped Learning Model
The Effect of the Flipped Learning Model on Spiritual Care Perception and Competence in Nursing Students
The Effect of the Flipped Learning Model on Nursing Students' Perception of Spiritual Care and Competence This study was designed as a randomised controlled trial to determine the effect of the flipped learning model on nursing…
- Trial name
- NCT07338253
- Testing
- flipped learning model
- Where
- Turkey (Türkiye)
- Volunteers
- 112 people, healthy volunteers welcome
- Sponsor
- Kırıkkale University
Flipped Education Model, Self Directed Learning
Effects of 'Evidence-based Practice' Training Based on Flipped Learning, Web-based and Traditional Education Models on Nurses' Self-directed Learning and Metacognitive Thinking Skills
The research was conducted to evaluate the effects of evidence-based practice training developed based on flipped learning, web-based education and traditional education models on nurses' self-directed learning and metacognitive…
- Conditions
- Flipped Education Model, Self Directed Learning, Metacognition, Web Based Education
- Trial name
- NCT06988891
- Testing
- 'Evidence-based practice' training based on the flipped learning model, 'Evidence-based practice' training based on web-based education model, 'Evidence-based practice' training based on traditional education model
- Where
- Turkey (Türkiye)
- Volunteers
- 45 people, healthy volunteers welcome
- Sponsor
- Istanbul University - Cerrahpasa
Cancer Diagnosis, Liver Cancer, Adult
Raman Spectroscopy-Based Deep Learning Model for Early Pan-Cancer Early Diagnosis
The goal of this observational study is to explore whether a Raman-based, deep learning-assisted approach can be used to develop an effective method for early pan-cancer screening.
- Conditions
- Cancer Diagnosis, Liver Cancer, Adult, Cancer Screening, Colorectal Cancer (CRC)
- Trial name
- NCT06822413
- Testing
- No Interventions
- Where
- 4 sites in China
- Volunteers
- 600 people, healthy volunteers welcome
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
Peripheral Vein, Arterial Wave Reflections
Deep Learning Model for Predicting a Peripheral Venous Waveform-based Pulse Pressure Variation
Pulse pressure variation is a monitoring index that indicates the response to fluid therapy in patients receiving mechanical ventilation, and is used as a reference for patients with unstable hemodynamic conditions.
- Conditions
- Peripheral Vein, Arterial Wave Reflections, Pulse Pressure Variation, Stroke Volume Variation
- Trial name
- NCT06734650
- Testing
- peripheral waveform collection
- Where
- South Korea
- Volunteers
- 150 people, healthy volunteers welcome
- Sponsor
- Seoul National University Bundang Hospital