Work

An AI-enabled tool for quantifying overlapping red blood cell sickling dynamics in microfluidic assays

Year: 2026

Type: article

Abstract: densely packed cell suspensions, capture drug-dependent sickling behavior, and reveal distinct mechanobiological signatures of cellular morphological evolution. Overall, this AI-driven framework establishes a scalable and reproducible computational platform for investigating cellular biomechanics and assessing therapeutic efficacy in microphysiological systems.

Source: Lab on a Chip

DOI: 10.1039/d6lc00108d

Authors: Nikhil Kadivar, Guansheng Li, Jianlu Zheng, Ming Dao, George Em Karniadakis, Mengjia Xu

Institutions: Brown University, Massachusetts Institute of Technology, New Jersey Institute of Technology

Language: English

Topic: Cell Image Analysis Techniques

Subfield: Biophysics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: hybrid

Funders: National Institutes of Health, National Heart, Lung, and Blood Institute