ascopubs.org

Development of an Automatic Rule-Based Algorithm for the Detection of Ovarian Cancer Recurrence From Electronic Health Records

The automatic rule-based recurrence detection algorithm (Auto-Recur), using notes on image reading (positron emission tomography-computed tomography [PET-CT], CT, magnetic resonance imaging [MRI]), ...
Nature

Robustly federated learning model for identifying high-risk patients with postoperative gastric cancer recurrence

The prediction of patient disease risk via computed tomography (CT) images and artificial intelligence techniques shows great potential. However, training a robust artificial intelligence model ...
Nature

A GRU–CNN model for auditory attention detection using microstate and recurrence quantification analysis

Attention as a cognition ability plays a crucial role in perception which helps humans to concentrate on specific objects of the environment while discarding others. In this paper, auditory attention ...
Medscape

Race and Ethnicity in CRC Recurrence Risk Algorithms?

Omitting race and ethnicity from colorectal cancer (CRC) recurrence risk prediction models could decrease their accuracy and fairness, particularly for minority groups, potentially leading to ...
Healio

Machine learning-based methods predict early-stage melanoma recurrence

Please provide your email address to receive an email when new articles are posted on . Researchers at Massachusetts General Hospital and Harvard Medical School have developed machine learning-based ...