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sepsis risk accuracyOhio State News
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89% Informative
SepsisLab was developed based on feedback from doctors and nurses who treat patients in the emergency departments and ICUs where sepsis is most commonly seen.
System identifies missing patient information, quantifies how essential it is.
System is designed to come up with a risk prediction quickly, but produces a new prediction every hour after new patient data has been added to the system.
The research was published Aug. 24 in KDD ' 24 : Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining .
Zhang has received additional NIH funding to continue collaborating with clinicians on this work.
Additional co-authors include Jeffrey Caterino of The Ohio State University Wexner Medical Center , Bingsheng Yao and Dakuo Wang of Northeastern University , and Pin-Yu Chen of IBM Research .
VR Score
91
Informative language
92
Neutral language
46
Article tone
formal
Language
English
Language complexity
71
Offensive language
not offensive
Hate speech
not hateful
Attention-grabbing headline
not detected
Known propaganda techniques
not detected
Time-value
long-living
External references
13
Source diversity
11
Affiliate links
no affiliate links