Nature

Deep learning for survival prediction in triple-negative breast cancer: development and validation in real-world cohorts

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous disease, highlighting the need for better patient stratification to guide treatment. We developed a deep learning-based survival ...
Nature

A deep learning dataset for metal multiaxial fatigue life prediction

Multiaxial fatigue failure of metals, a common issue in industrial production, often leads to significant losses. Recently, many researchers have applied deep learning methods to predict the ...
ascopubs.org

Development and validation of a deep learning clinical decision support system to optimize inpatient mortality and palliative care referrals in cancer patients.

The wasting shadow: Underweight/cachexia as a consistent predictor of adverse inpatient outcomes and escalated resource use across common solid tumors.
ascopubs.org

Development, comparative study, and external validation of a new deep learning model for predicting genome-wide gene expression from histopathology slides.

Analytical validation of the Labcorp Plasma Complete test to enable precision oncology through solid tumor liquid biopsy comprehensive genomic profiling. This is an ASCO Meeting Abstract from the 2024 ...
Neurology Advisor

Multimodal Deep Learning Model Improves CT-Based Alzheimer Disease Classification

A multimodal deep learning framework trained on paired CT and MRI data demonstrated improved diagnostic accuracy when classifying patients with Alzheimer disease, mild cognitive impairment, or normal ...
News Medical

UCSF collaborates with Intel to deploy and validate deep learning analytics to improve healthcare

UC San Francisco's Center for Digital Health Innovation (CDHI) today announced a collaboration with Intel Corporation to deploy and validate a deep learning analytics platform designed to improve care ...