Early and accurate prediction of neurological outcomes in comatose patients following cardiac arrest is critical for informed clinical decision-making. Existing studies have predominantly focused on ...

Explainable Artificial Intelligence (XAI) seeks to render the operation and decisions of complex machine learning systems transparent and interpretable to users, regulators and other stakeholders. As ...

Shekar Vollem, a Senior Software Engineer, researcher, inventor, peer reviewer, and technology leader whose work spans ...

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 ...

A machine learning (ML)-based model may aid in-hospital community-acquired pneumonia (CAP) mortality prediction, according to study findings published in Respiratory Medicine. Res ...

Using a real-world, nationwide electronic health record–derived deidentified database of 38,048 patients with advanced NSCLC, we trained binary prediction algorithms to predict likelihood of 12-month ...

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 ...

Breast cancer is a biologically heterogeneous disease in which genomic complexity, dynamic tumor evolution, and variable therapeutic response continue to ...

The terrestrial water cycle is a fundamental component of Earth's climate system, governing the exchange of water between land surfaces and the atmosphere.

This course explores the field of Explainable AI (XAI), focusing on techniques to make complex machine learning models more transparent and interpretable. Students will learn about the need for XAI, ...

In todays fast evolving financial landscape, artificial intelligence and machine learning are changin how credit decisions get made. But the traditional “black box” models cause worry 'cause nobody ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...