Using proteomics to predict long-term disability outcomes in MS
Data from protein analyses, combined with data from patient journals, enabled the discovery of proteins that predict disease progression.
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Data from protein analyses, combined with data from patient journals, enabled the discovery of proteins that predict disease progression.
Novel approaches to brain disorder diagnosis and treatment may be developed following a project to form a map of the mouse hippocampus.
A certain macrophage phenotype is more effective than another phenotype commonly used in cell therapy for infiltrating tumours.
Tune into this podcast to understand why researchers are turning to 3D Organoids and how organoids can be made ready for screening.
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.
Drug Target Review’s Taylor Mixides interviews Cellarity's CEO Fabrice Chouraqui about applying Artificial Intelligence (AI) and Machine Learning (ML) to evolving single-cell technologies.
27 June 2023 | By
In this eBook, uncover the transformative potential of AI/ML in single-cell technologies and gain insights into disease progression.
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.