Clinical trials: Prediction Model
Kidney Transplantation, Delirium - Postoperative
A Predictive Model for Postoperative Delirium in Kidney Transplant Patients
This study aims to develop and prospectively validate a machine learning-based prediction model for postoperative delirium in kidney transplant recipients, using perioperative clinical data.
- Conditions
- Kidney Transplantation, Delirium - Postoperative, Cognitive
- Trial name
- NCT07078578
- Volunteers
- 4,800 people
- Sponsor
- Hua Zheng
Moyamoya Disease, Moyamoya Syndrome
Development and Validation of Risk Prediction Models for Stroke and Cognitive Impairment in Moyamoya Disease and Moyamoya Syndrome
This multicenter prospective observational cohort study aims to develop and validate individualized risk prediction models for stroke and cognitive decline in patients with moyamoya disease or moyamoya syndrome by integrating…
- Trial name
- NCT07894107
- Where
- 13 sites in China
- Volunteers
- 3,000 people
- Sponsor
- Beijing Tiantan Hospital
Basal Cell Carcinoma
AI-Based Risk Classification and Histopathological Subtype Prediction of Basal Cell Carcinoma Using Dermoscopic Images
This retrospective observational study aims to develop and evaluate a convolutional neural network (CNN)-based artificial intelligence model for risk classification and histopathological subtype prediction of basal cell carcinoma…
- Trial name
- BCC-AI (NCT07677124)
- Where
- Turkey (Türkiye)
- Volunteers
- 2,500 people
- Sponsor
- Istanbul Training and Research Hospital
Congenital Heart Disease (CHD), Ventricular Septal Defects (VSD)
A Multimodal AI Prediction Model for Complications After Transcatheter Closure of Perimembranous VSD in Children
The goal of this observational study is to develop and validate a multimodal artificial intelligence prediction model for treatment-related complications in children with perimembranous ventricular septal defect (pmVSD)…
- Conditions
- Congenital Heart Disease (CHD), Ventricular Septal Defects (VSD), Cardiac Catheterization, Postoperative Complications
- Trial name
- NCT07375602
- Where
- China
- Volunteers
- 5,249 people
- Sponsor
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Chronic Pancreatitis, Pancreatic Neoplasm
Prediction Model of Pancreatic Neoplasms in CP Patients With Focal Pancreatic Lesions
This study aims to develop XGBoost machine learning model to predict pancreatic neoplasms in CP patients with focal pancreatic lesions.
- Conditions
- Chronic Pancreatitis, Pancreatic Neoplasm, Machine Learning
- Trial name
- NCT07045181
- Testing
- XGBoost machine learning
- Where
- China
- Volunteers
- 113 people
- Sponsor
- Changhai Hospital
Adult Congenital Heart Disease, Cardiac Surgery
Multicenter Validation of a Predictor Model of ACHD Patients and Cardiac Surgery
This multicentre study is to validate prediction modeling for the ACHD population undergoing cardiac surgery. The validation of this prediction model will support and generalize its use as a risk stratification tool in the ACHD…
- Trial name
- NCT04787705
- Where
- Canada
- Volunteers
- 547 people
- Sponsor
- University Health Network, Toronto
Epilepsy, Surgery--Complications
Complications After Epilepsy Surgery
Epilepsy surgery is effective for refractory epilepsy, particularly focal epilepsy, but is still underutilized worldwide. In the United States, the annual percentage of surgical procedures for refractory epilepsy was low (range…
- Trial name
- NCT04727892
- Testing
- epilepsy surgery
- Volunteers
- 2,026 people
- Sponsor
- First Affiliated Hospital Xi'an Jiaotong University
Ischemic Cerebrovascular Disease, Artificial Intelligence
Research on Early Prediction Model of Ischemic Cerebrovascular Disease Based on Artificial Intelligence Technology.
Establish an artificial intelligence clinical decision support system for patients with carotid/vertebral artery cerebrovascular stenosis, early identification of patients who may have cerebral infarction.
- Conditions
- Ischemic Cerebrovascular Disease, Artificial Intelligence, Prediction Model
- Trial name
- NCT06978348
- Where
- China
- Volunteers
- 244,296 people
- Sponsor
- Shanghai Jiao Tong University School of Medicine
Severe Malaria
Clinical Prediction Models for Pediatric In-Hospital Death Risk in Congolese Severe Malaria Children Using Machine Learning Based-Algorithms
The goal of this observational study is to optimize the management of severe childhood malaria, based on understanding and controlling the severity factors of the disease in Congolese children aged 2 to 9 years (the age group at…
- Trial name
- NCT07355426
- Testing
- Puncture of the radial artery for instant arterial blood gaz as well as for venous biochemistry
- Where
- Democratic Republic of the Congo
- Volunteers
- 100 people
- Sponsor
- University of Kinshasa
Sepsis
Establishment of Early Diagnosis and Monitoring Model for Sepsis Patients
In recent years, although the clinical treatment of sepsis has been greatly improved, it is still an important cause of death in ICU patients, and seriously threatens human health.
- Trial name
- EDAMMFS (NCT04974411)
- Testing
- infection, sepsis
- Where
- China
- Volunteers
- 2,000 people, healthy volunteers welcome
- Sponsor
- First Affiliated Hospital Xi'an Jiaotong 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
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
Artificial Intelligence, Septic Shock
Artificial Intelligence for Sepsis Prediction in ICU
The development of sepsis prediction model in line with Chinese population, and extended to clinical, assist clinicians for early identification, early intervention, has a good application prospect.
- Conditions
- Artificial Intelligence, Septic Shock, Intensive Care Unit Psychosis
- Trial name
- AICUSepsis (NCT04913181)
- Testing
- Artificial intelligence sepsis prediction model
- Volunteers
- 2,000 people
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
Healthcare; Risk Prediction; Diabetic Patients With Osteoporosis
A Model for Risk Prediction of Fracture in Diabetic Patients With Osteoporosis
The fracture risk of diabetic patients proves to be higher than those without diabetesdue to thehyperglycemia, usage of diabetes drugs, the changes in insulin levels and excretion, and this risk begins as early as…
- Trial name
- NCT04534166
- Testing
- Risk Prediction of Fracture in Diabetic Patients with Osteoporosis
- Sponsor
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Coronavirus Infection, COVID19
Prediction Models for Diagnosis and Prognosis of Severe COVID-19
Clinical observation has found that COVID-19 patients often present inconsistency of clinical features, nucleic acid of the SARS-CoV-2 and imaging findings, which brings challenges to the management of patients.The quantitative…
- Trial name
- NCT04525287
- Where
- 6 sites in China
- Volunteers
- 617 people
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
Hypoxemia, Obstructive Sleep Apnea
The Prediction Model of Hypoxemia for Safe Bronchoscopy
The purpose of this study is to develop the hypoxemia prediction model during fiberoptic bronchoscopy under MAC(monitored anesthesia care) anesthesia.
- Trial name
- NCT01370993
- Where
- South Korea
- Volunteers
- 150 people
- Sponsor
- Seoul National University Bundang Hospital
Intracranial Aneurysm
A Study on a Multidimensional Prediction Model for Rupture Risk of Unruptured Intracranial Aneurysms
This is a registry study on a multidimensional prediction model for rupture risk of unruptured intracranial aneurysms in China.
- Trial name
- CIAP-2 (NCT03133624)
- Where
- 12 sites in China
- Volunteers
- 500 people
- Sponsor
- Beijing Neurosurgical Institute
Orthodontic Appliance Complication
Accuracy of Digital Three-Dimensional Root Position Prediction Via Digitized Models
Measuring the accuracy of a new technique by which root positions can be predicted at the pre-finishing stage of the comprehensive orthoodntic treatment
- Trial name
- NCT03552640
- Where
- Egypt
- Volunteers
- 10 people
- Sponsor
- Cairo University
Acute Liver Failure
Etiology and Prognostic Factors in Patients With Acute Liver Failure
Acute liver failure (ALF) is a rare but life-threatening condition with high mortality. Despite advances in supportive care and liver transplantation, prognosis varies significantly across etiologies, particularly in patients…
- Trial name
- NCT07556055
- Volunteers
- 400 people
- Sponsor
- Li-Ying Sun
Recurrent Lumbar Disc Herniation
The Prediction of Recurrence Lumbar Disc Herniation At L5-S1 Level Through Machine Learning Models Based on Endoscopic Discectomy Via the Interlaminar Approach
What Was the Study About? This study focused on improving the care of patients with a specific type of back problem called lumbar disc herniation at the L5-S1 level.
- Trial name
- NCT06833099
- Testing
- VAS Point and Imaging Examination
- Where
- China
- Volunteers
- 309 people
- Sponsor
- Jinyu Chen