Research scientist @UCSDHealth working on improving healthcare delivery using machine learning. Formerly: PhD @GeorgiaTech, @MSFTResearch, @qualcomm_in
San Diego, CA
Joined June 2016
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Thanks @AmazonScience for covering our work on development of early sepsis prediction model at @UCSDHealth!
Special shoutout to my wonderful mentors @ShamimNemati @AtulMalhotra13 @WardiGabriel!
How can ML help hospitals detect sepsis? Using a model built by @UCSDHealth research scientist @spshash, clinicians have an early warning of patients predicted to develop sepsis in the next four hours. Learn how #AmazonResearchAwards helped scale the life-changing service.
Supreeth Shashikumar retweeted
Building the NexGen predictive models in healthcare:
go.nature.com/4mgy5u9
Supreeth Shashikumar retweeted
🚨 New study alert! Wearable devices + multiscale entropy = better prediction of unplanned hospital readmissions. Promising step for AI in healthcare! #AI #Wearables #HealthcareInnovation
Great work by @vishal15n @WardiGabriel @spshash @AtulMalhotra13
academic.oup.com/jamia/artic…
Supreeth Shashikumar retweeted
4/5 In an ER setting, ordering of blood culture is often followed by administration of antibiotics, therefore it's not clear if providers will wait for a AI risk score to initiate treatments for sepsis. Moreover, all cases without a clinical suspicion of sepsis will be missed!
Supreeth Shashikumar retweeted
Great working with @ABoussina @spshash @AtulMalhotra13 @ShamimNemati to get this important work out there! That you for highlighting this important work on #sepis and #ai in healthcare!
For a patient with sepsis, the speed of diagnosis is a matter of life or death. @WardiGabriel, MD, emergency medicine physician, helped create an #AI system to spot people at high risk of #sepsis at #UCSDHealth. #HealthCare kpbs.org/news/science-techno…
Supreeth Shashikumar retweeted
New article! Read Integrating artificial intelligence into healthcare systems: more than just the algorithm dlvr.it/T3V94C in npj Digital Med
Very excited to share our latest work showing improvement in sepsis-related outcomes (in-hospital sepsis related mortality, sepsis bundle compliance and 72h SOFA change) after real-world deployment of COMPOSER AI platform! 1/2
Can a novel #DeepLearning algorithm to predict #sepsis in the emergency department improve care?
Researchers from @UCSDHealth show proper implementation of the model can save lives of sepsis patients and improve quality metrics.
nature.com/articles/s41746-0…
Grateful to be working with a stellar team at @UCSDHealth to make this translational work a reality.
@ABoussina @ShamimNemati @WardiGabriel @AtulMalhotra13 @DrBobOwens @CALonghurst 2/2
related news coverage: today.ucsd.edu/story/study-a…
One of the few studies in the field of sepsis related predictive analytics reporting improvement in outcomes after real world deployment of an AI based deep learning model for early sepsis prediction. 1/2
1/3 Healcisio's AI Reduces Sepsis Mortality By Nearly 20%: NIH Funded Healcisio Collaboration Advances the Development o... prn.to/3HtVMMb #AI #Sepsis #MedTwitter
Incredible excited that our team @healcisio is leading such translational efforts in AI in Medicine. 2/2
Supreeth Shashikumar retweeted
1/4 Deployment of COMPOSER AI platform was associated with a 1.9% absolute reduction (17% relative decrease) in in-hospital #sepsis mortality, a 5.0% absolute increase (10% relative increase) in sepsis bundle compliance, and a 4% reduction in 72h SOFA change after sepsis onset.
Can a novel #DeepLearning algorithm to predict #sepsis in the emergency department improve care?
Researchers from @UCSDHealth show proper implementation of the model can save lives of sepsis patients and improve quality metrics.
nature.com/articles/s41746-0…
Supreeth Shashikumar retweeted
Great collaborative effort with @ShamimNemati @spshash @ABoussina to put this forward. And huge thanks to the wonderful residents @UCSDEMResidency for attending the presentation at #ACEP23!
Supreeth Shashikumar retweeted
MCoPet (Mobile Companion Pet) can now talk in different languages, communicate with #EHR via #FHIR, connect to #wearables & #IoT devices, and analyze a host of inclusive and insightful personal health-related data via #ArtificialIntelligence.
Voice-Enabled Response Analysis Agent (VERAA): Leveraging Large Language Models to Map Voice Responses in SDoH Survey medrxiv.org/cgi/content/shor… #medRxiv
Supreeth Shashikumar retweeted
Great seeing the recognition the best #ML researchers out there are getting! @spshash @FatemehAmrollah @ShamimNemati and how their work is saving lives! @AtulMalhotra13 @CALonghurst
amazon.science/research-awar…
Supreeth Shashikumar retweeted
Great article by our #AWS partner featuring the Amazon Research Award winner @spshash & the brain behind our #sepsis #AI & quality improvement efforts @UCSDHealth:
amazon.science/research-awar…
Thanks to @beckersHR for highlighting our efforts in using #AI for early #sepsis prediction @UCSDHealth! A true team effort with @CALonghurst @ShamimNemati @ABoussina @AtulMalhotra13 to get this going! @ucsdpccsm @SepsisAlliance
beckershospitalreview.com/in…
Supreeth Shashikumar retweeted
Interested in how to make your predictive models more clinically relevant? Check out our viewpoint on strategies to do this in @CritCareMed! @ShamimNemati @CALonghurst @AtulMalhotra13 @DrBobOwens
journals.lww.com/ccmjournal/…
Supreeth Shashikumar retweeted
Nice work by @FatemehAmrollah, @spshash, @NathanYungMDMS showing wearable data can predict #sepsis readmissions @CALonghurst @AtulMalhotra13
Predicting Hospital Readmission among Patients with Sepsis using Clinical and Wearable Data medrxiv.org/content/10.1101/…
Supreeth Shashikumar retweeted
1/4) >$4.6 billion in excess cost savings for CMS! Check out this interesting work by @parker_rog and colleagues: "Optimizing the Implementation of Clinical Predictive Models to Minimize National Costs: A Sepsis Case Study": preprints.jmir.org/preprint/… #digitalhealth via @jmirpub
