Research scientist @UCSDHealth working on improving healthcare delivery using machine learning. Formerly: PhD @GeorgiaTech, @MSFTResearch, @qualcomm_in

San Diego, CA
Joined June 2016
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.

1
1
8
1,591
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…
6
1
20
2,077
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!
1
1
2
354
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!
1
2
10
733
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…
1
7
763
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
1
1
6
191
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
2
140
Incredible excited that our team @healcisio is leading such translational efforts in AI in Medicine. 2/2
1
32
Supreeth Shashikumar retweeted
2/4 The composer platform leverages #FHIR and #AWS cloud to enable real-time predictive analytics for various clinical scenarios, such as sepsis, respiratory failure, and deterioration, among others. It also integrates with existing #EHR systems and clinical workflows.
1
1
6
233
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…
5
11
1
44
9,055
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!
3
1
1
26
2,193
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
4
16
2,402
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…
2
3
13
4,080
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/…
6
11
1,504
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/…
2
1
8
778
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
1
5
1
19
4,093