When machine learning models deliver problematic results, it can often happen in ways that humans can't make sense of, and this becomes dangerous when there are no limitations of the model, ...

Artificial intelligence may be able to do more than predict what happens after prostate cancer surgery; it can also help doctors understand which factors are shaping those predictions. A new study, ...

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 ...

Lung cancer (LC) is a leading cause of cancer-related mortality in the United States. Accurate prediction of LC mortality rates is crucial for guiding targeted interventions and addressing health ...

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, ...

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 ...

Machine learning is a branch of AI focused on building computer systems that learn from data. The breadth of ML techniques enables software applications to improve their performance over time. ML ...

Enabled Intelligence (EI), the leader in high-precision AI data labeling, and Seekr, the leader in explainable, defensible AI, today announced a partnership to bring greater speed and efficiency to ...