Aliro: an automated machine learning tool leveraging large language models

被引:1
|
作者
Choi, Hyunjun [1 ]
Moran, Jay [1 ]
Matsumoto, Nicholas [1 ]
Hernandez, Miguel E. [1 ]
Moore, Jason H. [1 ,2 ]
机构
[1] Cedars Sinai Med Ctr, Ctr Artificial Intelligence Res & Educ, Dept Computat Biomed, Hollywood, CA 90069 USA
[2] Cedars Sinai Med Ctr, Ctr Artificial Intelligence Res & Educ, Pacific Design Ctr, Dept Computat Biomed, 700 N San Vicente Blvd,Suite G-541H, West Hollywood, CA 90069 USA
基金
美国国家卫生研究院;
关键词
D O I
10.1093/bioinformatics/btad606
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation Biomedical and healthcare domains generate vast amounts of complex data that can be challenging to analyze using machine learning tools, especially for researchers without computer science training.Results Aliro is an open-source software package designed to automate machine learning analysis through a clean web interface. By infusing the power of large language models, the user can interact with their data by seamlessly retrieving and executing code pulled from the large language model, accelerating automated discovery of new insights from data. Aliro includes a pre-trained machine learning recommendation system that can assist the user to automate the selection of machine learning algorithms and its hyperparameters and provides visualization of the evaluated model and data.Availability and implementation Aliro is deployed by running its custom Docker containers. Aliro is available as open-source from GitHub at: https://github.com/EpistasisLab/Aliro.
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页数:4
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