Clinical trials: Predictive Learning Models
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
Sexually Transmitted Infections (STIs), HIV
Development of a Predictive Model for Sexually Transmitted Infections in Individuals Using Pre-Exposure Prophylaxis for HIV in Spain
Objective: To develop and validate a predictive model for acquiring sexually transmitted infections (STIs) in individuals using HIV pre-exposure prophylaxis (PrEP) within the national program providing this strategy.
- Conditions
- Sexually Transmitted Infections (STIs), HIV, PrEP
- Trial name
- STI_PrEPare (NCT06860945)
- Testing
- No Intervention: Observational Cohort
- Where
- 26 sites in Spain
- Volunteers
- 9,000 people, healthy volunteers welcome
- Sponsor
- Hospital Universitario de Valme
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