Why Your 'Accurate' AI Model Might Still Be Dangerously Wrong: The Hidden Importance Of Model Calibration

Trustworthy AI isn’t just about predicting the right outcome; it’s about knowing how confident we should actually be.
Dermatology Advisor

Factors Predicting Super Response to Rituximab for Pemphigus Identified

Several factors have been identified that may predict super response or refractory response to rituximab among patients with pemphigus.
Frontiers

Comparison of multiple machine learning methods for predicting postoperative hyperglycemia in patients without diabetes undergoing cardiac surgery

Background: Stress-induced hyperglycemia (SHG) represents a significant metabolic complication in non-diabetic cardiac surgery older adult patients, with substantial implications for postoperative ...
C&EN

Porous-Structure Flexible Muscle Sensor for Monitoring Muscle Function and Mass

Muscle function and composition are important indicators of age-related health. However, current assessment methods are often complex and expensive, making the early detection of related problems ...
IEEE

Flood Hazard Prediction Model Based on K-means Clustering Analysis and AdaBoost Regression Model

Abstract: In this paper, data analysis and predictive modeling are used as tools to explore the pattern of flood hazard occurrence and provide early warning support. First, indicators with high ...
Frontiers

Leveraging machine learning to optimize cooling tower efficiency for sustainable power generation

United Nations Sustainable Development Goal 7 is about ensuring access to clean and affordable energy, which is a key factor in the development of society. The power generation sector majorly consists ...
Visual Studio Magazine

AdaBoost Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the AdaBoost.R2 algorithm for regression problems (where the goal is to predict a single numeric value). The ...