Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic ...
Frontiers

Deep Learning for Medical Imaging Applications

Artificial Intelligence (AI) is revolutionizing the dynamics of technological advancement in the field of medical imaging, ...
EurekAlert!

Yonsei University researchers develop deep learning model for microsatellite instability-high tumor prediction

One in every three people is expected to have cancer in their lifetime, making it a major health concern for mankind. A crucial indicator of the outcome of cancer is its tumor microsatellite ...
Frontiers

AI and Imaging for Oral Cancer Diagnosis and Prognosis

The integration of artificial intelligence (AI) with imaging has emerged as a transformative force in the field of oral oncology. Oral cancer remains a ...
ascopubs.org

Deep learning–powered H&E whole-slide image analysis of endothelial cells to characterize tumor vascular environment and correlate treatment outcome to immunotherapy.

Completed phase 1a dose escalation study of the first oral ENPP1 inhibitor RBS2418 immunotherapy in subjects with metastatic solid tumors. SECN-15: A novel treatment option for patients with ...
EurekAlert!

Deep learning model helps detect lung tumors on CT

Model and clinical segmentation examples. (A) 71-year-old female with non-small cell lung cancer (NSCLC) from the internal test set. (B) 87-year-old male with NSCLC from the external test set. Both ...
European Medical Journal

AI Pathology Transforms NSCLC Molecular Triage

Deep-learning analysis of routine H&E slides accurately predicts key NSCLC driver mutations, supporting treatment in lung cancer care.
ascopubs.org

Analysis of Tumor Microenvironmental Features Between Primary and Synchronous Liver Metastases From Patients With Colorectal Cancers Using a Deep Learning Algorithm

Adult patients with CRC with synchronous CRLM (N = 57) at Mayo Clinic were identified from the electronic health record. Routine tumor hematoxylin and eosin sections were digitized and reviewed for ...
Macmillan Cancer Support

Cancer prognosis and prediction

This article explores how advances in data, genomics and artificial intelligence are improving our ability to estimate ...
technologynetworks

Brain Cancer Digital Twin Predicts Whether a Treatment Is Likely To Slow Tumor Growth

A new machine-learning-based approach to mapping real-time tumor metabolism in brain cancer patients, developed at the University of Michigan, could help doctors discover which treatment strategies ...