BindsNET: A Machine Learning-Oriented Spiking Neural Networks Library in Python von Hazan, Hananel, Saunders, Daniel J, Khan, Hassaan, Patel, Devdhar, Sanghavi, Darpan T, Siegelmann, Hava T, Kozma, Robert

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Lattice map spiking neural networks (LM-SNNs) for clustering and classifying image data von Hazan, Hananel, Saunders, Daniel J., Sanghavi, Darpan T., Siegelmann, Hava, Kozma, Robert

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122 Quantification of tumor infiltrating lymphocytes (TILs) from pathology slides reflects molecular immune phenotypes von Shen, Ciyue, Nofallah, Shima, Conway, Jake, Parmar, Chintan, Drage, Michael G, Najdawi, Fedaa, Sanghavi, Darpan T, Yu, Limin, Biju, Raymond, Borders, Daniel, Bronnimann, Matthew, Chambre, Laura, Finberg, Issac, Glickman, Jonathan, Griffin, Michael, Gupta, Sidharth, Harguindeguy, Natalia, Le, Nhat, Hennek, Stephanie, Javed, Syed Ashar, Kirkup, Christian, Markey, Miles, Nercessian, Michael, Shenker, Daniel, Srinivasan, Sandhya, Valaboju, Vignesh, Mercedes, Samuel AV, Rahsepar, Bahar, Leung, Ryan, Khosla, Archit, Glass, Benjamin, Taylor-Weiner, Amaro, Gerardin, Ylaine, Abel, John

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110 Deep learning models identify key tumor microenvironment features associated with genetic signatures of UV mutagenesis and alkylating agent treatment in melanoma von Nofallah, Shima, Sanghavi, Darpan T, Gupta, Sidharth, Shen, Ciyue, Le, Nhat, Yu, Limin, Rahsepar, Bahar, Leung, Ryan, Glass, Benjamin, Taylor-Weiner, Amaro, Gerardin, Ylaine, Abel, John, Conway, Jake

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Lattice Map Spiking Neural Networks (LM-SNNs) for Clustering and Classifying Image Data von Hazan, Hananel, Saunders, Daniel J, Sanghavi, Darpan T, Siegelmann, Hava, Kozma, Robert

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BindsNET: A machine learning-oriented spiking neural networks library in Python von Hazan, Hananel, Saunders, Daniel J, Khan, Hassaan, Sanghavi, Darpan T, Siegelmann, Hava T, Kozma, Robert

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Unsupervised Learning with Self-Organizing Spiking Neural Networks von Hazan, Hananel, Saunders, Daniel J, Sanghavi, Darpan T, Siegelmann, Hava T, Kozma, Robert

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Lattice Map Spiking Neural Networks (LM-SNNs) for Clustering and Classifying Image Data von Hazan, Hananel, Saunders, Daniel J, Sanghavi, Darpan T, Siegelmann, Hava, Kozma, Robert

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AI powered quantification of nuclear morphology in cancers enables prediction of genome instability and prognosis von Abel, John, Jain, Suyog, Rajan, Deepta, Padigela, Harshith, Leidal, Kenneth, Prakash, Aaditya, Conway, Jake, Nercessian, Michael, Kirkup, Christian, Javed, Syed Ashar, Biju, Raymond, Harguindeguy, Natalia, Shenker, Daniel, Indorf, Nicholas, Sanghavi, Darpan, Egger, Robert, Trotter, Benjamin, Gerardin, Ylaine, Brosnan-Cashman, Jacqueline A., Dhoot, Aditya, Montalto, Michael C., Parmar, Chintan, Wapinski, Ilan, Khosla, Archit, Drage, Michael G., Yu, Limin, Taylor-Weiner, Amaro

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PLUTO: Pathology-Universal Transformer von Juyal, Dinkar, Padigela, Harshith, Shah, Chintan, Shenker, Daniel, Harguindeguy, Natalia, Liu, Yi, Martin, Blake, Zhang, Yibo, Nercessian, Michael, Markey, Miles, Finberg, Isaac, Luu, Kelsey, Borders, Daniel, Javed, Syed Ashar, Krause, Emma, Biju, Raymond, Sood, Aashish, Ma, Allen, Nyman, Jackson, Shamshoian, John, Chhor, Guillaume, Sanghavi, Darpan, Thibault, Marc, Yu, Limin, Najdawi, Fedaa, Hipp, Jennifer A, Fahy, Darren, Glass, Benjamin, Walk, Eric, Abel, John, Pokkalla, Harsha, Beck, Andrew H, Grullon, Sean

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Improved statistical benchmarking of digital pathology models using pairwise frames evaluation von Gerardin, Ylaine, Shamshoian, John, Shen, Judy, Le, Nhat, Prezioso, Jamie, Abel, John, Finberg, Isaac, Borders, Daniel, Biju, Raymond, Nercessian, Michael, Prasad, Vaed, Lee, Joseph, Wyman, Spencer, Gupta, Sid, Emerson, Abigail, Rahsepar, Bahar, Sanghavi, Darpan, Leung, Ryan, Yu, Limin, Khosla, Archit, Taylor-Weiner, Amaro

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PLUTO: Pathology-Universal Transformer von Juyal, Dinkar, Padigela, Harshith, Shah, Chintan, Shenker, Daniel, Harguindeguy, Natalia, Liu, Yi, Blake, Martin, Zhang, Yibo, Nercessian, Michael, Markey, Miles, Finberg, Isaac, Luu, Kelsey, Borders, Daniel, Syed Ashar Javed, Krause, Emma, Biju, Raymond, Sood, Aashish, Ma, Allen, Nyman, Jackson, Shamshoian, John, Chhor, Guillaume, Sanghavi, Darpan, Thibault, Marc, Yu, Limin, Najdawi, Fedaa, Hipp, Jennifer A, Fahy, Darren, Glass, Benjamin, Walk, Eric, Abel, John, Pokkalla, Harsha, Beck, Andrew H, Grullon, Sean

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Improved statistical benchmarking of digital pathology models using pairwise frames evaluation von Gerardin, Ylaine, Shamshoian, John, Shen, Judy, Le, Nhat, Prezioso, Jamie, Abel, John, Finberg, Isaac, Borders, Daniel, Biju, Raymond, Nercessian, Michael, Prasad, Vaed, Lee, Joseph, Wyman, Spencer, Gupta, Sid, Emerson, Abigail, Rahsepar, Bahar, Sanghavi, Darpan, Leung, Ryan, Yu, Limin, Khosla, Archit, Taylor-Weiner, Amaro

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