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 ...

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 ...

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, ...

A practical review of explainable AI examines how transparency and interpretability improve trust in high-stakes ...

An area of great hope and promise for applied artificial intelligence (AI) deep learning is at the intersection of neuroscience and oncology, both challenging fields known for their inherent ...

Protein language models are artificial intelligence tools which help engineer proteins with useful properties, including completely new structures never seen before in nature. The technology has huge ...

The hydrologic system is subjected unprecedented stresses and increasing demands driven by climate variabilities, landuse changes, groundwater ...