Toward a Team of AI-made Scientists for Scientific Discovery from Gene Expression Data

arXiv:2402.12391v1 Announce Type: cross
Abstract: Machine learning has emerged as a powerful tool for scientific discovery, enabling researchers to extract meaningful insights from complex datasets. For instance, it has facilitated the identification of disease-predictive genes from gene expression data, significantly advancing healthcare. However, the traditional process for analyzing such datasets demands substantial human effort and expertise for the data selection, processing, and analysis. To address this challenge, we introduce a novel framework, a Team of AI-made Scientists (TAIS), designed to …

abstract arxiv cs.ai cs.lg data datasets discovery disease enabling extract gene genes healthcare identification insights instance machine machine learning predictive process q-bio.gn researchers scientific discovery scientists team tool type