Clinical trials: Predictive Learning Models
Acute Ischemic Stroke
Prognostic Prediction Model of Patients With AcUte Stroke undeRgoing EndOvascular TheRApy (AURORA)
Stroke is the leading cause of disability-adjusted life years (DALYs) in China, imposing a heavy burden on society and families.
- Trial name
- AURORA (NCT06009315)
- Where
- China
- Volunteers
- 949 people
- Sponsor
- Beijing Tiantan Hospital
Posterior Fossa Tumors, Pediatric Tumor of Brain
Predicting Cognitive Dysfunction After Pediatric Posterior Fossa Tumor Surgery
The goal of this observational study is to develop and validate a clinical prediction model to identify risk factors for long-term cognitive dysfunction in children (ages 0-18 years) who have undergone surgical resection of a…
- Trial name
- NCT07350382
- Testing
- Not applicable- observational study
- Where
- China
- Volunteers
- 600 people
- Sponsor
- West China Hospital
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
Colorectal Cancer Liver Metastases (CRLM)
AI-Based Prediction of Liver Metastasis in Colorectal Cancer (A Retrospective Study)
This multicenter, retrospective study aims to develop and validate a multimodal deep learning model for predicting the risk of metachronous liver metastasis in patients with stage I-III colorectal cancer following curative…
- Trial name
- NCT07399236
- Testing
- Multimodal Deep Learning Model Analysis
- Where
- China
- Volunteers
- 1,500 people
- Sponsor
- Tongji Hospital
Palliative Care
Impact of Predictive Modeling on Time to Palliative Care in an Outpatient Primary Care Population
A machine learning algorithm will be used to accurately identify patients in certain primary care units who may benefit from palliative care consults.
- Trial name
- NCT04604457
- Testing
- Palliative care contacts primary care
- Where
- United States
- Volunteers
- 127,070 people
- Sponsor
- Mayo Clinic
Venous Thromboembolism (VTE), Occult Cancer
External Validation of the CLOVER Score for Detecting Occult Cancer in Venous Thromboembolism Patients
This study aims to externally validate the CLOVER score, a machine learning-based predictive model designed to identify patients with venous thromboembolism (VTE) who are at increased risk of having an occult cancer.
- Trial name
- CLOVER (NCT07310693)
- Where
- 12 sites in Spain
- Volunteers
- 500 people
- Sponsor
- Infanta Leonor University Hospital
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
Rotator Cuff Tears
Machine Learning Predictive Model for Rotator Cuff Repair Failure
There is little overall evidence behind clinical practice guidelines for diagnosis and treatment of rotator cuff repair. The purpose of this study was to compare the performance of different machine learning models that use…
- Trial name
- NCT06145815
- Testing
- Arthroscopic rotator cuff repair
- Where
- Switzerland
- Volunteers
- 4,789 people
- Sponsor
- La Tour Hospital
Non-small Cell Lung Cancer Metastatic
Predictive Multimodal Signatures Associated With Response to Treatment and Prognosis of Patients With Stage IV Non-small Cell Lung Cancer
Predicting response to therapy and disease progression in stage IV NSCLC patients treated with pembrolizumab monotherapy, chemotherapy-pembrolizumab combination therapy or chemotherapy alone in the first-line setting.
- Trial name
- DEEP-Lung-IV (NCT04994795)
- Testing
- Predictive models (data collection)
- Where
- 30 sites in United States, Brazil and 6 more
- Volunteers
- 4,000 people
- Sponsor
- Sophia Genetics SAS
Hepatocellular Carcinoma (HCC), Artificial Intelligent
Construction and Clinical Validation of a Predictive Model for Postoperative Adjuvant Therapy in Hepatocellular Carcinoma Based on Whole-Slide Digital Pathological Images and Deep Learning
Hepatocellular carcinoma (HCC) is a high-mortality global malignancy with a heavy disease burden in China. Although curative surgical resection improves survival for early-stage HCC patients, the 5-year postoperative recurrence…
- Conditions
- Hepatocellular Carcinoma (HCC), Artificial Intelligent, Adjuvant Chemoradiotherapy, TACE
- Trial name
- NCT07417800
- Testing
- AI adjuvant therapy
- Where
- China
- Volunteers
- 11,000 people
- Sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine