EurekAlert!

Interpretable AI unlocks new thermal material frontiers

The calculation and/or the measurement of the thermal conductivity of materials is a fundamental challenge in materials science, essential for developing technologies in energy management, electronics ...
ZDNet

Explainable AI: From the peak of inflated expectations to the pitfalls of interpreting machine learning models

Machine learning and artificial intelligence are helping automate an ever-increasing array of tasks, with ever-increasing accuracy. They are supported by the growing volume of data used to feed them, ...
ascopubs.org

Interpretable Machine Learning Models for Predicting Lateral Pelvic Lymph Node Metastasis in Rectal Cancer: A Chinese Multicenter Retrospective Study

Clinical Interchangeability of PD-L1 Immunohistochemistry Assays in First-Line Non–Small Cell Lung Cancer Management With Cemiplimab Internal iliac and obturator lymph nodes are common sites of ...
ZDNet

Explainable AI: A guide for making black box machine learning models explainable

Machine learning is taking the world by storm, helping automate more and more tasks. As digital transformation expands, the volume and coverage of available data grows, and machine learning sets its ...
ascopubs.org

AI/ML-derived mechanistically interpretable whole-genome biomarkers of patient survival in pre-treatment primary neuroblastoma tumors and whole blood.

Institutional review of pediatric oncology patients participating in early phase clinical trials. This is an ASCO Meeting Abstract from the 2024 ASCO Annual Meeting I. This abstract does not include a ...
National Academies of Sciences%2c Engineering%2c and Medicine

Machine Learning and Artificial Intelligence to Advance Earth System Science: Opportunities and Challenges: Proceedings of a Workshop

In the context of the active use of ML/AI for Earth system science, many conceptual, technical, educational, and cultural challenges remain, as well as emerging approaches and opportunities to address ...