The Lancet

Large-scale profiling of blood microbial signatures in patients with Parkinson's disease and its association with disease progression: a cross-sectional study

aBioinformatics Center, National Clinical Research Center for Geriatric Diseases, Department of Geriatrics, Xiangya Hospital & Center for Medical Genetics, School of Life Sciences, Central South ...
Analytics Insight

Best Neural Networks Courses in 2026 for AI and Deep Learning

Overview Neural networks courses in 2026 focus heavily on practical deep learning frameworks such as TensorFlow, PyTorch, and Keras.Growing demand for AI profes ...
Analytics Insight

Best PyTorch Courses to Learn Deep Learning in 2026

PyTorch is one of the most popular tools for building AI and deep learning models in 2026.The best PyTorch courses teach both basic concept ...
IEEE

Waveform Classification and Loss Prediction Based on Principal Component Analysis and Decision Tree

Abstract: In this paper, a waveform classification method based on principal component analysis and decision tree and a loss prediction model with improved Steinmetz equation are proposed, focusing on ...
IEEE

Optimized Predictive Technique for Intelligent Classification (OPTIC): A Decision Tree Ensemble Approach for Neurodegenerative Disease Detection via Gait Pattern Analysis

Abstract: Purpose of the Study: Neurodegenerative diseases such as Parkinson’s, Alzheimer’s, and Huntington’s progressively impair motor and cognitive functions, making early detection essential for ...
GitHub

A minimal, secure Python interpreter written in Rust for use by AI.

Experimental - This project is still in development, and not ready for the prime time. A minimal, secure Python interpreter written in Rust for use by AI. Monty avoids the cost, latency, complexity ...
Frontiers

A clinical prediction model for delirium tremens: development and validation in alcohol-dependent patients using multivariable logistic regression

Delirium tremens (DT) is a severe complication of alcohol withdrawal. This study aimed to develop and validate a prediction model for DT risk in hospitalized patients with alcohol dependence, using ...