BRAINX COMMUNITY, a group of experts in machine learning, healthcare and innovation has grown to be 2000+ international member strong since its inception in May 2018.

Dr. Avirup Guha will be conducting a journal club on a recent JAMA article titled : “How to Read Articles That Use Machine Learning: Users’ Guides to the Medical Literature – by  Liu et al” (JAMA. 2019;322(18):1806-1816. doi:10.1001/jama.2019.16489).

 Dr. Guha is a cardiologist at the Harrington Heart and Vascular
Institute and Assistant Professor of Medicine at Case Western Reserve University. Dr. Guha completed his Cardiology fellowship at the Ohio State University. He is board certified in cardiovascular disease and multiple cardiac imaging modalities. Dr. Guha is an expert in cardio-oncology and is widely published in that field. His research focuses on using traditional statistical models in studying cardiovascular outcomes using large national datasets. He is a programmer in SAS and has been programming in Python recently to create a tweetbot for covering literature in the field of cardio-oncology. Dr. Guha has published more than 60 peer-reviewed manuscripts, scientific abstracts, and book chapters. He is highly collaborative with his current research spanning over 8-9 national and international institutions. Dr. Guha is a peer-reviewer for Journal of American Heart Association, Journal of American College of Cardiology, JACC: CardioOncology among others. Dr. Guha believes in the theory of being trilingual i.e. all physicians working in the field of population and clinical research should expertly communicate ideas between clinical colleagues, biostatisticians and data scientists to increase efficiency of research and development of tools for taking care of patients. 

For more details, BrainX Community platform is available through https://www.brainxai.org and LinkedIn group called BrainX Community. No registration, no fees, refreshments provided and open invite to all! Please feel free to share with friends and colleagues.

BRAINX COMMUNITY LIVE ! PROGRAM

January 22, 2020,5:00-6:15 PM EST .ONLINE ONLY.

Now through zoom online.Join us via link below.

Piyush Mathur is inviting you to a scheduled Zoom meeting.

Topic: BrainX Community Live!
Time: Jan 22, 2020 05:00 PM Eastern Time (US and Canada)

Join Zoom Meeting
https://zoom.us/j/813385455?pwd=T3BHZC9BQVFpa2FHTXhWYzAwRnJvZz09

Meeting ID: 813 385 455
Password: 459123

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Meeting ID: 813 385 455
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Agenda

5:00-5:05 PM: BrainX Community live!

5:05-5:10 PM: Drivers Unplugged. Dr. Avirup Guha

5:10-6:15 PM: Journal club : “How to Read Articles That Use Machine Learning: Users’ Guides to the Medical Literature – by  Liu et al” .Dr. Avirup Guha

 

 

New sections on BrainX Community  launched

New sections called Journals and Meetings.

Journals lists and provides links to journals focused on  machine learning in healthcare.Available on right sidebar of webpage.

Meetings lists and provides links to meetings focused on machine learning in healthcare.

Contact us to get your journal or meeting listed.

BrainX Community Europe Launch

Learn more about our growing community expanding into Europe thanks to Tomasz ROGULA, MD, PhD, FACS , Klaudia PRONIEWSKA, PhD, Eng. , Aneta MYSZKA, MD ,Jacek CYWINSKI, MD  and Nasit VURGUN, MD.

Learn more about our efforts and join us in supporting the growth of this community.Growing organically with a common purpose, vision and mission to scientifically promote knowledge expansion in the field of machine learning applications for  healthcare.

 

A guide to getting started with machine learning in healthcare

A simple but exclusive 14 step guide compiled by members of BrainX Community to help get started with machine learning in healthcare.

Learning the basic programming skills, resources needed to get started on a project and more are all outlined in this simple guide.

Most importantly, it's a primer in getting bilingual and fostering collaboration between healthcare professionals and machine learning experts.

BrainX Community 

Facts and Figures

1500+ international members:Largest online community for machine learning in healthcare.

24+ countries.

16 Live monthly monthly sessions since May 2018.

Largest repository of data sources links.

Single place for curated  machine learning in healthcare scientific articles.

Diversity in membership including Medical Students, Computer Science Graduate and Postgraduate Students, Physicians, Data Scientists, AI/ML Academicians, University Professors, Inventors, Innovation Managers, Entrepreneurs and even High School Students! 

One  vision

Machine Learning in healthcare for good.

One mission

Connect, learn and share scientific knowledge about applications of Machine Learning in healthcare.

One ask

Connect and Contribute