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Zhanghan Yin on Muck Rack

Zhanghan Yin

As seen in: Nature
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Articles

An AI-powered self-driving microscope for low-cost acute leukemia detection

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By Ethan Yan, Shenghuan Sun, Zhanghan Yin, Ali Reza Kamali, Jacob G. Van Cleave, Irem S. Isgor, Brenda Fried, Cesar Colorado-Jimenez, Deepika Dilip, Jeeyeon Baik, Allyne Manzo, Sean Paulsen, Siddharth Singi, Scott Drapeau, Özgür EREN, Aijazuddin Syed, Anthony Cardillo, Melissa Pulitzer, Maly Fenelus, David Kim, Jamal Benhamida, Dianna Ng, Orly Ardon, Ahmet Dogan, Chad Vanderbilt, Khawaja Bilal, Gregory Goldgof, Joanne K. Chun, Mikhael Roshal
| Nature Verified
Abstract Current artificial intelligence systems for leukemia detection typically rely on costly whole-slide scanners, limiting accessibility in low-resource settings. We present ALLocate, a low-cost, artificial intelligence-powered microscope plugin that enables self-driving microscopy for leukemia detection. ALLocate attaches directly to conventional microscopes and provides automated analysis at a fraction of the cost of a whole-slide scanner.
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Interpretable multiple instance learning for hematologic diagnosis from peripheral blood smears

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By Siddharth Singi, Shenghuan Sun, RIYA Gupta, Khawaja Bilal, Deepika Dilip, Linlin Wang, Neeraj Kumar, Nicolas Sanchez, Nicolás Galarza Sánchez, Sean Paulsen, Ethan Yan, Ali Reza Kamali, Jeeyeon Baik, Anthony Cardillo, Leonardo Boiocchi, Aijazuddin Syed, Brie E. Kezlarian-Sachs, Maly Fenelus, Alexander Chan, Mariko Yabe, Menglei Zhu, Simon Mantha, Orly Ardon, Wenbin Xiao, Mikhail Roshal, Oscar Lin, Ahmet Dogan, Iain Carmichael, Chad Vanderbilt, Gregory Goldgof, Zhanghan Yin, Swaraj Nanda, Jacob G. Van Cleave, Brenda Fried, Argho Sarkar, Allyne Manzo, Irem S. Isgor, Cesar Colorado-Jimenez, Samuel I. McCash, Lauren McVoy
| Nature Verified
Abstract Accurate diagnosis of hematologic malignancies from peripheral blood smears (PBSs) requires integrating cellular morphology and composition across numerous white blood cells. Existing computational approaches predominantly automate single-cell classifications and do not provide holistic, slide-level diagnostic predictions.
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