Objective Breastfeeding prevalence and challenges among women of systemic lupus erythematosus (SLE) and rheumatoid arthritis ...

The author investigates how probabilistic classification can be used to enhance credit-scoring accuracy, offering a robust means for assessing model performance ...

Scientists have developed and tested a deep-learning model that could support clinicians by providing accurate results and ...

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to ...

Microsoft on Tuesday announced an autonomous artificial intelligence (AI) agent that can analyze and classify software without assistance in an effort to advance malware detection efforts. The large ...

Background: Early identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood ...

Recently, many machine learning techniques have been presented to detect brain lesions or determine brain lesion types using microwave data. However, there are limited studies analyzing the location ...

Reasoning models are an attempt to further boost AI's accuracy using a process known as "chain-of-thought." It works by tracing patterns through this data using multi-step responses, mimicking how ...

Logistic regression is the most cost-effective model for medial vascular calcification classification, with a mean ICER of $278 using five low-cost features. Despite similar diagnostic accuracy, ...

This repository provides an efficient binary video classification pipeline using PyTorch, optimized for local GPU-enabled PCs. It includes preprocessing and model inference tools for classifying ...