This article examines the work of data scientist Sai Prashanth Pathi in AI for credit risk, focusing on explainable machine ...

Discover how explainable AI enhances Parkinson’s disease prediction with improved accuracy and clinical interpretability.

Analysis of the 191 samples shows that 55 percent of groundwater falls within low to no restriction categories for irrigation ...

In past roles, I’ve spent countless hours trying to understand why state-of-the-art models produced subpar outputs. The underlying issue here is that machine learning models don’t “think” like humans ...

This retrospective study included 643 patients who had undergone NSCLC resection. ML models (random forest, gradient boosting, extreme gradient boosting, and AdaBoost) and a random survival forest ...

Recent research is advancing seismic hazard modeling through AI-driven soil liquefaction prediction, interpretable machine learning, physics-based simulations, and waveform-based probabilistic ...

In a significant breakthrough, researchers have developed an advanced explainable deep learning model to predict and analyze harmful algal blooms (HABs) in freshwater lakes and reservoirs across China ...

This new study addresses this gap by integrating advanced machine learning models with explainable AI techniques, enabling both high predictive performance and biological insight. A broad range of ...

Head and neck cancers represent a biologically heterogeneous group of malignancies requiring accurate diagnosis, staging, and risk stratification for ...