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Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

The message from leading indicators is of a broad-based and strengthening recovery in the global economy at the start of 2026, pointing to at least 6 months of robust coincident data ahead.

Discover how AI is transforming nutritional science by turning complex diet and omics data into predictive tools that reshape chronic disease prevention and personalized care.

A recent analysis of thousands of social media posts reveals that losing a job alters the narrative landscape of a person’s ...

This study proposes a cross-species transcriptomic framework to predict vaccine reactogenicity, with implications for preclinical vaccine safety assessment. The findings show that mouse muscle ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Discover how proteomics data analysis and bioinformatics tools enhance mass spectrometry workflows for robust findings.

Abstract: Early fault classification using the Motor Current Signature Analysis approach is extremely challenging for many reasons: prior knowledge of the descriptive parameters of the acquired stator ...

Mount Sinai experts to present new analysis on AI models that could predict congenital heart defects and placenta accreta spectrum at the 2026 SMFM Annual Pregnancy Meeting ...

Explore technical features and comparative strengths of MaxQuant, Proteome Discoverer, FragPipe, and DIA-NN workflows.

Abstract: Objective: To determine the characteristics of a building after a natural disaster using image input through the integration of image analysis techniques. Methods: Several image analysis ...