Novel approaches to brain disorder diagnosis and treatment may be developed following a project to form a map of the mouse hippocampus.
List view / Grid view
A certain macrophage phenotype is more effective than another phenotype commonly used in cell therapy for infiltrating tumours.
Artificial intelligence (AI) and machine learning (ML) have been gaining significant attention lately, primarily in discussions about their responsible utilisation. However, these technologies possess a wide spectrum of practical applications, ranging from predicting natural disasters to addressing social disparities. Now, AI is making its mark in the field of cancer…
Rob Scoffin and Matthew Habgood from solutions provider Cresset look to the future of drug discovery and the roles that artificial intelligence and machine learning could play.
Machine learning (ML) presents a promising opportunity to revolutionize early cancer detection in primary care, addressing the challenges associated with diagnostic errors and improving patient outcomes. The potential of ML in this field is highlighted in a recent paper published in Oncoscience
Cornell University launches $11.3 Million Scientific Artificial Intelligence Centre to unlock the potential of human-AI collaboration in scientific discoveries.
In this article, Drug Target Review's Ria Kakkad and Izzy Wood explore the results of the latest research on lab automation techniques and technologies designed to accelerate drug discovery.
US researchers, using new machine learning techniques have developed a virtual molecular library of “words” that encode commands to kill cancer cells.