Bhavna Daryani: Using Technology to Make Anemia Screening More Accessible and Non-Invasive
Bhavna Daryani, Lead Clinical Research Operations Program Manager at Google, shared Matthew Thompson‘s on LinkedIn, adding:
“Proud to have been part of this impactful research collaboration!
Exciting to see how technology and clinical research can come together to make anemia screening more accessible, scalable, and non-invasive, particularly in underserved communities.
Grateful to have contributed alongside such a dedicated team and incredible collaborators at SEWA Rural, with support from the Gates Foundation.”
Matthew Thompson, Clinical Research Scientist at Google, shared a post on LinkedIn about a recent article he and his colleagues co-authored, adding:
“How accurately can smartphones detect anemia?
Published in pre-print this week, excited to share this landmark study, a multi-year effort, funded also by the Gates foundation and with remarkable collaborators at SEWA Rural in Gujarat, India.
Final results?
Very large data set of 5176 adults (including pregnant women) and children, including 711 with severe anemia.
Final model, using Samsung smartphone images of conjunctiva, showed sensitivity 90% and specificity 80% to detect severe anemia vs moderate, mild, or no anemia.”
Title: Smartphone-based Non-Invasive Classification of Anemia Severity using Deep Learning: A Cross-Sectional Study in Rural India
Authors: Shrey Desai, Shruti Gadgil, Vineel Abhinav Gottala, Kaushal Jesalpura, Divya Ramnath, Elzbieta Gruzewska, Harshad Purandare, Yun Liu, Umesh Telang, James A. Taylor, Rajroshan Sawhney, Richa Tiwari, Dale R. Webster, Shravya Shetty, Avinatan Hassidim, Yossi Matias, Michael Howell, Sethuraman Venkatraman, Bhavna Daryani, Christina Chen, Sujay Kakarmath, Mayank Daswani, Marc Wilson, Raghu Pullakhandam, Swapnil Vispute, Matthew Thompson
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