Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...
A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...
In the article that accompanies this editorial, Bergstrom et al 7 present DeepHRD, a deep learning (DL) algorithm that predicts homologous recombination deficiency and clinical outcomes directly from ...
Can deep learning catch chronic illness before symptoms show? This article explores how time-aware neural networks are reshaping early detection and care planning for conditions like diabetes and COPD ...
ctDNA test, which is an important aspect in liquid biopsy, offers a non-invasive alternative to tissue biopsies for cancer diagnosis and monitoring. Ultra-deep ctDNA sequencing enabling the detection ...
A leading expert in AI-driven healthcare innovation, Mahesh Recharla has proposed a new approach to identify Multiple Sclerosis (MS) and Alzheimer’s disease (AD) in their earliest, often asymptomatic ...
Max Delbrück Center for Molecular Medicine in the Helmholtz Association Altuna Akalin and his team at the Max Delbrück Center have developed a new tool to more precisely guide cancer treatment.
BioCompNet: a dual-channel deep learning framework for automated body composition analysis from fat-water MRI sequences. (A) Schematic of the dual-channel 2-dimensional (2D) U-Net architecture used to ...
Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...
The staggering computational demands of AI have become impossible to ignore. McKinsey estimates that training an AI model costs $4 million to $200 million per training run. The environmental impact is ...
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