Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...
Abstract: Tabular data is the most prevalent form of structured data, necessitating robust models for classification and regression tasks. Traditional models like eXtreme Gradient Boosting (XGBoost) ...
Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
This project addresses the problem of predicting water levels in fish ponds - a critical factor in aquaculture management. Using Machine Learning, we can: Predict water levels based on environmental ...
From movement detection to real-time adjustments, the process shows how robotics mimic natural human motion. Alex Pretti spotted on camera moments before fatal shooting in Minneapolis Enormous ...
Abstract: In the practical scenario of Federated Learning (FL), clients upload their local model to a server at different times owing to heterogeneity in the clients’ device environment. Therefore, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results