Dima Shulkin: Next-Generation AI Models Improve Early Sepsis Recognition
Dima Shulkin, Co-Founder and CTO at RobotDreams GmbH, shared a post on LinkedIn about a recent article by Tai-Han Lin et al, published in Journal of Medical Internet Research, adding:
“What if a routine blood test could flag a deadly infection in minutes instead of days?
A 2025 study by Lin and colleagues, published in the JMIR Publications, trained AI to spot sepsis (a life-threatening overreaction to infection that causes about 1 in 5 deaths worldwide) using only a standard blood count.
Looking back at records from 746 intensive care patients and 746 healthy outpatients in Taiwan, the best AI scored 0.90 out of 1.0 at telling sick from healthy.”
Title: AI-Driven Innovations for Early Sepsis Detection by Combining Predictive Accuracy With Blood Count Analysis in an Emergency Setting: Retrospective Study
Authors: Tai-Han Lin, Hsing-Yi Chung, Ming-Jr Jian, Chih-Kai Chang, Hung-Hsin Lin, Chiung-Tzu Yen, Sheng-Hui Tang, Pin-Ching Pan, Cherng-Lih Perng, Feng-Yee Chang, Chien-Wen Chen, Hung-Sheng Shang
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