Jenny C. Chang։ AI Identifies Hidden Patterns in Bloodstream Infections
Jenny C. Chang, President and CEO of Houston Methodist Academic Institute, and EVP and Chief Academic Officer at Houston Methodist, shared a post on LinkedIn:
“A new Houston Methodist study, published in the American Journal of Transplantation and led by Masayuki Nigo, associate professor of medicine, found that artificial intelligence can assist in identifying previously unseen infection patterns.
Patients with bloodstream infections – including solid organ transplant recipients – are not clinically uniform despite sharing the same diagnosis.
Dr. Nigo noted, ‘Using routinely collected data from the first 48 hours of infection, we identified three distinct clinical patterns based on patient characteristics, illness severity, and organ support through a machine learning-based clustering approach.’
We appreciate the contributions of our outstanding research team and collaborators.”
Stay updated with Hemostasis Today.
-
Apr 14, 2026, 16:02EU List of Critical Medicines Webinar Recording Now Available – EHC
-
Apr 14, 2026, 15:54Omar Adwan: Patterns of Anemia
-
Apr 14, 2026, 15:43Webinar on Aplastic Anemia Clinical Case – ASH
-
Apr 14, 2026, 15:42Heghine Khachatryan: Endometriosis Is Not Only a Pain Disorder
-
Apr 14, 2026, 15:36Alisha Tuck: Navigating the First Trimester with Ultrasound and Anticoagulation Management
-
Apr 14, 2026, 15:26Tijjani Balas: The End of ‘Type O Negative’ Shortages? – A New Era in Blood Transfusion
-
Apr 14, 2026, 15:07Carlos Henrique Del Carlo: HFpEF Reimagined as an Adipose Tissue Driven Disease
-
Apr 14, 2026, 15:05Matteo Foschi: ASPERA-R Study Reveals Competing Causes Of Breakthrough Stroke On Anticoagulation
-
Apr 14, 2026, 14:48Samwel Mikaye: From Virchow’s Triad to Prevention of PE in Patients with DVT