Long-Term Recurrent Convolutional Networks for Visual Recognition and Description von Donahue, Jeff, Hendricks, Lisa Anne, Rohrbach, Marcus, Venugopalan, Subhashini, Guadarrama, Sergio, Saenko, Kate, Darrell, Trevor

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Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs von Gulshan, Varun, Peng, Lily, Coram, Marc, Stumpe, Martin C, Wu, Derek, Narayanaswamy, Arunachalam, Venugopalan, Subhashini, Widner, Kasumi, Madams, Tom, Cuadros, Jorge, Kim, Ramasamy, Raman, Rajiv, Nelson, Philip C, Mega, Jessica L, Webster, Dale R

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Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning von Varadarajan, Avinash V., Bavishi, Pinal, Ruamviboonsuk, Paisan, Chotcomwongse, Peranut, Venugopalan, Subhashini, Narayanaswamy, Arunachalam, Cuadros, Jorge, Kanai, Kuniyoshi, Bresnick, George, Tadarati, Mongkol, Silpa-archa, Sukhum, Limwattanayingyong, Jirawut, Nganthavee, Variya, Ledsam, Joseph R., Keane, Pearse A., Corrado, Greg S., Peng, Lily, Webster, Dale R.

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Detection of anaemia from retinal fundus images via deep learning von Mitani, Akinori, Huang, Abigail, Venugopalan, Subhashini, Corrado, Greg S., Peng, Lily, Webster, Dale R., Hammel, Naama, Liu, Yun, Varadarajan, Avinash V.

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Integrating deep learning and unbiased automated high-content screening to identify complex disease signatures in human fibroblasts von Schiff, Lauren, Migliori, Bianca, Chen, Ye, Carter, Deidre, Bonilla, Caitlyn, Hall, Jenna, Fan, Minjie, Tam, Edmund, Ahadi, Sara, Fischbacher, Brodie, Geraschenko, Anton, Hunter, Christopher J., Venugopalan, Subhashini, DesMarteau, Sean, Narayanaswamy, Arunachalam, Jacob, Selwyn, Armstrong, Zan, Ferrarotto, Peter, Williams, Brian, Buckley-Herd, Geoff, Hazard, Jon, Goldberg, Jordan, Coram, Marc, Otto, Reid, Baltz, Edward A., Andres-Martin, Laura, Pritchard, Orion, Duren-Lubanski, Alyssa, Daigavane, Ameya, Reggio, Kathryn, Nelson, Phillip C., Frumkin, Michael, Solomon, Susan L., Bauer, Lauren, Aiyar, Raeka S., Schwarzbach, Elizabeth, Noggle, Scott A., Monsma, Frederick J., Paull, Daniel, Berndl, Marc, Yang, Samuel J., Johannesson, Bjarki

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Using large language models to accelerate communication for eye gaze typing users with ALS von Cai, Shanqing, Venugopalan, Subhashini, Seaver, Katie, Xiao, Xiang, Tomanek, Katrin, Jalasutram, Sri, Morris, Meredith Ringel, Kane, Shaun, Narayanan, Ajit, MacDonald, Robert L., Kornman, Emily, Vance, Daniel, Casey, Blair, Gleason, Steve M., Nelson, Philip Q., Brenner, Michael P.

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A machine-learning based objective measure for ALS disease severity von Vieira, Fernando G., Venugopalan, Subhashini, Premasiri, Alan S., McNally, Maeve, Jansen, Aren, McCloskey, Kevin, Brenner, Michael P., Perrin, Steven

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Topic based classification and pattern identification in patents von Venugopalan, Subhashini, Rai, Varun

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Scientific Discovery by Generating Counterfactuals Using Image Translation von Narayanaswamy, Arunachalam, Venugopalan, Subhashini, Webster, Dale R., Peng, Lily, Corrado, Greg S., Ruamviboonsuk, Paisan, Bavishi, Pinal, Brenner, Michael, Nelson, Philip C., Varadarajan, Avinash V.

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Author Correction: Detection of anaemia from retinal fundus images via deep learning von Mitani, Akinori, Huang, Abigail, Venugopalan, Subhashini, Corrado, Greg S., Peng, Lily, Webster, Dale R., Hammel, Naama, Liu, Yun, Varadarajan, Avinash V.

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Applying Deep Neural Network Analysis to High-Content Image-Based Assays von Yang, Samuel J., Lipnick, Scott L., Makhortova, Nina R., Venugopalan, Subhashini, Fan, Minjie, Armstrong, Zan, Schlaeger, Thorsten M., Deng, Liyong, Chung, Wendy K., O’Callaghan, Liadan, Geraschenko, Anton, Whye, Dosh, Berndl, Marc, Hazard, Jon, Williams, Brian, Narayanaswamy, Arunachalam, Ando, D. Michael, Nelson, Philip, Rubin, Lee L.

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Predicting the risk of developing diabetic retinopathy using deep learning von Bora, Ashish, Balasubramanian, Siva, Babenko, Boris, Virmani, Sunny, Venugopalan, Subhashini, Mitani, Akinori, de Oliveira Marinho, Guilherme, Cuadros, Jorge, Ruamviboonsuk, Paisan, Corrado, Greg S, Peng, Lily, Webster, Dale R, Varadarajan, Avinash V, Hammel, Naama, Liu, Yun, Bavishi, Pinal

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Batch equalization with a generative adversarial network von Qian, Wesley Wei, Xia, Cassandra, Venugopalan, Subhashini, Narayanaswamy, Arunachalam, Dimon, Michelle, Ashdown, George W, Baum, Jake, Peng, Jian, Ando, D Michael

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Detection of anaemia from retinal fundus images via deep learning (vol 4, pg 18, 2019) von Mitani, Akinori, Huang, Abigail, Venugopalan, Subhashini, Corrado, Greg S., Peng, Lily, Webster, Dale R., Hammel, Naama, Liu, Yun, Varadarajan, Avinash V.

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TRILLsson: Distilled Universal Paralinguistic Speech Representations von Shor, Joel, Venugopalan, Subhashini

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Detection of anaemia from retinal fundus images via deeplearning von Mitani Akinori, Huang, Abigail, Venugopalan Subhashini, Corrado, Greg S, Peng, Lily, Webster, Dale R, Hammel Naama, Liu, Yun, Varadarajan, Avinash V

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SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers von Pramanick, Shraman, Chellappa, Rama, Venugopalan, Subhashini

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Applying Deep Neural Network Analysis to High-Content Image-Based Assays von Yang, Samuel J., Lipnick, Scott L., Makhortova, Nina R., Venugopalan, Subhashini, Fan, Minjie, Armstrong, Zan, Schlaeger, Thorsten M., Deng, Liyong, Chung, Wendy K., O’Callaghan, Liadan, Geraschenko, Anton, Whye, Dosh, Berndl, Marc, Hazard, Jon, Williams, Brian, Narayanaswamy, Arunachalam, Ando, D. Michael, Nelson, Philip, Rubin, Lee L.

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Parameter Efficient Tuning Allows Scalable Personalization of LLMs for Text Entry: A Case Study on Abbreviation Expansion von Tomanek, Katrin, Cai, Shanqing, Venugopalan, Subhashini

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SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers von Pramanick, Shraman, Chellappa, Rama, Venugopalan, Subhashini

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