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Frontiers

Advanced Computational Approaches For Data And Model Integration In Bioinformatic and Biomedical Research

In the rapidly evolving field of computational intelligence, there is a pressing demand for advanced tools and algorithms ...

Using deep learning for precision cancer therapy

Nearly 50 new cancer therapies are approved every year. This is good news. "But for patients and their treating physicians, ...
Frontiers

In Silico Drug Discovery and Drug-Designing in Combatting Antibiotic Resistance

Antibiotic resistance has emerged as one of the gravest global health challenges of the 21st century, undermining the effectiveness of available treatments ...

How massive datasets generated are powering the latest AI models in biology

In June, Google DeepMind took the wraps off AlphaGenome, its latest machine learning model for biological discovery. While ...
Technology Networks

Deep Learning Tool Helps Guide Precision Cancer Therapy

Researchers have developed a new tool to more precisely guide cancer treatment. Described in a paper published in Nature ...

From Few Samples to Thousands! MachineLearningLM Equips Large Models with a 'Machine Learning Engine' for Contextual Learning

Although large language models (LLMs) possess extensive world knowledge and strong reasoning capabilities, and are widely regarded as excellent few-shot learners, they still exhibit significant ...
Morning Overview on MSN

AI discovers new antibiotics in record time

The field of artificial intelligence (AI) is now revolutionizing the medical sector, particularly in the discovery of new antibiotics. Thanks to AI, new antibiotics have been discovered in a fraction ...
ascopubs.org

Prediction of CCL2 in breast cancer based on enhanced MRI radiomics model with integrated bioinformatics analysis and machine learning.

Exploring factors impacting quality of life in patients with breast cancer undergoing adjuvant hormone therapy: Experience of the Medical Oncology Department-CHU Hassan II-FEZ University Hospital.
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...