Dataset created for the purpose of continuing research into COVID-19. However with information from all 50 states and the District of Columbia, many US statistics can be compared.
Open access to all.
BrainX Community Youtube presentation video available now.
A review of 3000+ articles on machine learning in healthcare published in 2019 with specialist reviews.
A BrainX Community exclusive!
On April 28,2020, Srinivas R Mummadi, MD, presented the 2019 Year in Review:Machine Learning in Healthcare.
Watch the presentation video on BrainX Community's Youtube channel.
This is a BrainX Community exclusive where we will go over review of all the literature published on ML/AI in healthcare for the year 2019.
Dr. Mummadi is a Staff Physician at the Respiratory Institute and Medical Director of Clinical Informatics, Cleveland Clinic Foundation, OH. He has formal training background and is board certified in Internal Medicine, Pulmonary and Critical Care Medicine, Clinical Informatics and Medical Quality. He has interests in using informatics to improve health care quality and analyzing large outcomes databases. Clinical interests include obstructive lung disease and pleural disease.
COVID-19 datasets and challenges
With the evolving COVID-19 pandemic, new datasets and challenges have been made available on Kaggle.Let's join hands and commit to solving this crisis.
In response to the COVID-19 pandemic, the White House and a coalition of leading research groups have prepared the COVID-19 Open Research Dataset (CORD-19). CORD-19 is a resource of over 29,000 scholarly articles, including over 13,000 with full text, about COVID-19, SARS-CoV-2, and related coronaviruses.
From World Health Organization - On 31 December 2019, WHO was alerted to several cases of pneumonia in Wuhan City, Hubei Province of China.
This dataset has daily level information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this is a time series data and so the number of cases on any given day is the cumulative number.
The data is available from 22 Jan, 2020.
BrainX Community Live: YouTube channel
BrainX Community launches YouTube channel to promote education and collaboration for application of machine learning in healthcare.
We have moved our meeting events online to enhance participation by members all over the world and make content available through Youtube.
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.
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.
Facts and Figures
2000+ international members:Largest online community for machine learning in healthcare.
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!
Machine Learning in healthcare for good.
Connect, learn and share scientific knowledge about applications of Machine Learning in healthcare.
Connect and Contribute
Keep visiting us as we are developing this on a daily basis.
Join us on LinkedIn.Group name: BrainX Community