From a1eae7ec0d00e16df23c7ee87ddcf9a7bac7e7f9 Mon Sep 17 00:00:00 2001 From: Jay Moran Date: Thu, 17 Nov 2022 19:15:52 +0000 Subject: [PATCH] Updated About section and case on Readme --- README.md | 44 ++++++++++++++++++++++---------------------- 1 file changed, 22 insertions(+), 22 deletions(-) diff --git a/README.md b/README.md index dc06f3a17..92761f7d5 100644 --- a/README.md +++ b/README.md @@ -1,47 +1,47 @@ -[![logo](./docs/source/_static/logo_blank_small.png)]() +[![Logo](./docs/source/_static/logo_blank_small.png)]() -[![license: gpl v3](https://img.shields.io/badge/license-gpl%20v3-blue.svg)](https://github.com/epistasislab/aliro/blob/master/license) [![aliro ci/cd](https://github.com/epistasislab/aliro/actions/workflows/aliro_tests.yml/badge.svg)](https://github.com/epistasislab/aliro/actions/workflows/aliro_tests.yml) [![coverage status](https://coveralls.io/repos/github/epistasislab/pennai/badge.svg)](https://coveralls.io/github/epistasislab/pennai) +[![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://github.com/EpistasisLab/Aliro/blob/master/LICENSE) [![Aliro CI/CD](https://github.com/EpistasisLab/Aliro/actions/workflows/aliro_tests.yml/badge.svg)](https://github.com/EpistasisLab/Aliro/actions/workflows/aliro_tests.yml) [![Coverage Status](https://coveralls.io/repos/github/EpistasisLab/pennai/badge.svg)](https://coveralls.io/github/EpistasisLab/pennai) -aliro: ai-driven data science +Aliro: AI-Driven Data Science ================================== -**aliro** is an easy-to-use data science assistant. -it allows researchers without machine learning or coding expertise to run supervised machine learning analysis through a clean web interface. -it provides results visualization and reproducible scripts so that the analysis can be taken anywhere. -and, it has an *ai* assistant that can choose the analysis to run for you. dataset profiles are generated and added to a knowledgebase as experiments are run, and the ai assistant learns from this to give more informed recommendations as it is used. aliro comes with an initial knowledgebase generated from the [pmlb benchmark suite](https://github.com/epistasislab/penn-ml-benchmarks). +**Aliro** is an easy-to-use data science assistant. +It allows researchers without machine learning or coding expertise to run supervised machine learning analysis through a clean web interface. +It provides results visualization and reproducible scripts so that the analysis can be taken anywhere. +And, it has an *AI* assistant that can choose the analysis to run for you. Dataset profiles are generated and added to a knowledgebase as experiments are run, and the AI assistant learns from this to give more informed recommendations as it is used. Aliro comes with an initial knowledgebase generated from the [PMLB benchmark suite](https://github.com/EpistasisLab/penn-ml-benchmarks). -[**documentation**](https://epistasislab.github.io/aliro/) +[**Documentation**](https://epistasislab.github.io/Aliro/) -[**latest production release**](https://github.com/epistasislab/aliro/releases/latest) +[**Latest Production Release**](https://github.com/EpistasisLab/Aliro/releases/latest) -browse the repo: - - [user guide](./docs/guides/userguide.md) - - [developer guide](./docs/guides/developerguide.md) +Browse the repo: + - [User Guide](./docs/guides/userGuide.md) + - [Developer Guide](./docs/guides/developerGuide.md) -about the project +About the Project ================= -aliro is actively developed by the Center for Artificial Intelligence Research (CAIR) in the [Department of Computational Biomedicine](https://www.cedars-sinai.edu/research/departments-institutes/computational-biomedicine.html) at [Cedars-Sinai Medical Center](https://www.cedars-sinai.org/) in Los Angeles. +Aliro is actively developed by the Center for Artificial Intelligence Research (CAIR) in the [Department of Computational Biomedicine](https://www.cedars-sinai.edu/research/departments-institutes/computational-biomedicine.html) at [Cedars-Sinai Medical Center](https://www.cedars-sinai.org/) in Los Angeles. Contributors include Hyunjun Choi, Miguel Hernandez, Nick Matsumoto, Jay Moran, Paul Wang, and Jason Moore (PI). -cite +Cite ==== -an up-to-date paper describing ai methodology is available in [bioinformatics](https://doi.org/10.1093/bioinformatics/btaa698) and [arxiv](http://arxiv.org/abs/1905.09205). -here's the biblatex: +An up-to-date paper describing AI methodology is available in [Bioinformatics](https://doi.org/10.1093/bioinformatics/btaa698) and [arxiv](http://arxiv.org/abs/1905.09205). +Here's the biblatex: ``` @article{pennai_2020, - title = {evaluating recommender systems for {ai}-driven biomedical informatics}, + title = {Evaluating recommender systems for {AI}-driven biomedical informatics}, url = {https://doi.org/10.1093/bioinformatics/btaa698}, - journaltitle = {bioinformatics}, + journaltitle = {Bioinformatics}, doi = {10.1093/bioinformatics/btaa698}, year = {2020}, - author = {la cava, william and williams, heather and fu, weixuan and vitale, steve and srivatsan, durga and moore, jason h.}, + author = {La Cava, William and Williams, Heather and Fu, Weixuan and Vitale, Steve and Srivatsan, Durga and Moore, Jason H.}, eprinttype = {arxiv}, eprint = {1905.09205}, - keywords = {computer science - machine learning, computer science - information retrieval}, + keywords = {Computer Science - Machine Learning, Computer Science - Information Retrieval}, } ``` -you can also find our original position paper on [arxiv](https://arxiv.org/abs/1705.00594). +You can also find our original position paper on [arxiv](https://arxiv.org/abs/1705.00594).