A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases ...

Background Digital therapeutics (DTx) show promise in bridging mental healthcare gaps. However, treatment selection often relies on availability and trial-and-error, prolonging suffering and ...

A machine learning-based model can predict 30-day in-hospital mortality among patients with asthma in the ICU.

1. From 'Simulating Humans' to 'Data-Driven': The Ultimate Goal and Implementation Path of AI ...

Background Machine learning based on clinical characteristics has the potential to predict coronary CT angiography (CCTA) findings and help guide resource utilisation.Methods From the SCOT-HEART ...

What if plants could speak when they were thirsty? Agriculture, in essence, is a dialog among crops, soil and climate. Yet drought, the most insidious stressor, remains largely silent until its damage ...

The artificial intelligence method was used to optimize an early cancer detection test to ensure high sensitivity and specificity.

Engineered nanozymes and explainable machine learning enable sensitive bacterial detection across complex conditions. The system uses three distinct signals and delivers transparent, verifiable ...

The most successful institutions won't see artificial intelligence as merely an efficiency tool but as a responsibility to ...

1. Background and Significance of Public Opinion Monitoring ...

Overview: Free datasets are essential for practice, research, and AI model development.Platforms like Kaggle, UCI, and Google Dataset Search remain top choices ...

In an age where data drives decisions and automation defines excellence, the insurance industry stands at the cusp of a digital renaissance. At the ...