Nature

The optimization path of agricultural industry structure and intelligent transformation by deep learning

The primary objective of this study is to propose a deep learning-based approach for optimizing the agricultural industry structure, with the aim of addressing resource waste and environmental ...
Nature

A community effort to optimize sequence-based deep learning models of gene regulation

A systematic evaluation of how model architectures and training strategies impact genomics model performance is needed. To address this gap, we held a DREAM Challenge where competitors trained models ...

Microsoft’s open-source SkillOpt automatically upgrades AI agent skills without touching model weights

Microsoft's SkillOpt brings deep-learning discipline to AI agent skills, replacing manual prompt tweaking with mathematically ...
news.ucsb.edu

Proving the value of an old algorithm in training deep-learning models for AI

For about a decade, computer engineer Kerem Çamsari employed a novel approach known as probabilistic computing. Based on probabilistic bits (p-bits), it’s used to solve an array of complex ...
ascopubs.org

Optimizing chemotherapy decisions in low-resource settings with deep learning: A novel approach for unresectable NSCLC.

Validating a semantic similarity approach for automated data extraction in phase II oncology trials. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...
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.