Low-thrust rendezvous trajectory generation for multi-target active space debris removal using the RQ-Law von Narayanaswamy, Sanjeev, Wu, Benjamin, Ludivig, Philippe, Soboczenski, Frank, Venkataramani, Karthik, Damaren, Christopher J.

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Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study von Soboczenski, Frank, Trikalinos, Thomas A, Kuiper, Joël, Bias, Randolph G, Wallace, Byron C, Marshall, Iain J

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State of the evidence: a survey of global disparities in clinical trials von Marshall, Iain James, L'Esperance, Veline, Marshall, Rachel, Thomas, James, Noel-Storr, Anna, Soboczenski, Frank, Nye, Benjamin, Nenkova, Ani, Wallace, Byron C

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Trialstreamer: A living, automatically updated database of clinical trial reports von Marshall, Iain J, Nye, Benjamin, Kuiper, Joël, Noel-Storr, Anna, Marshall, Rachel, Maclean, Rory, Soboczenski, Frank, Nenkova, Ani, Thomas, James, Wallace, Byron C

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An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval von Cobb, Adam D., Himes, Michael D., Soboczenski, Frank, Zorzan, Simone, O'Beirne, Molly D., Güne Baydin, At l m, Gal, Yarin, Domagal-Goldman, Shawn D., Arney, Giada N., Angerhausen, Daniel

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In a pilot study, automated real-time systematic review updates were feasible, accurate, and work-saving von Marshall, Iain J., Trikalinos, Thomas A., Soboczenski, Frank, Yun, Hye Sun, Kell, Gregory, Marshall, Rachel, Wallace, Byron C.

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Accurate Machine-learning Atmospheric Retrieval via a Neural-network Surrogate Model for Radiative Transfer von Himes, Michael D., Harrington, Joseph, Cobb, Adam D., Güneş Baydin, Atılım, Soboczenski, Frank, O’Beirne, Molly D., Zorzan, Simone, Wright, David C., Scheffer, Zacchaeus, Domagal-Goldman, Shawn D., Arney, Giada N.

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Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document Summarization von Wallace, Byron C, Saha, Sayantan, Soboczenski, Frank, Marshall, Iain J

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Biomonitoring and precision health in deep space supported by artificial intelligence von Scott, Ryan T., Sanders, Lauren M., Antonsen, Erik L., Hastings, Jaden J. A., Park, Seung-min, Mackintosh, Graham, Reynolds, Robert J., Hoarfrost, Adrienne L., Sawyer, Aenor, Greene, Casey S., Glicksberg, Benjamin S., Theriot, Corey A., Berrios, Daniel C., Miller, Jack, Babdor, Joel, Barker, Richard, Baranzini, Sergio E., Beheshti, Afshin, Chalk, Stuart, Delgado-Aparicio, Guillermo M., Haendel, Melissa, Hamid, Arif A., Heller, Philip, Jamieson, Daniel, Jarvis, Katelyn J., Kalantari, John, Khezeli, Kia, Komarova, Svetlana V., Komorowski, Matthieu, Kothiyal, Prachi, Mahabal, Ashish, Manor, Uri, Garcia Martin, Hector, Mason, Christopher E., Matar, Mona, Mias, George I., Myers, Jerry G., Nelson, Charlotte, Oribello, Jonathan, Parsons-Wingerter, Patricia, Prabhu, R. K., Qutub, Amina Ann, Rask, Jon, Saravia-Butler, Amanda, Saria, Suchi, Singh, Nitin Kumar, Snyder, Michael, Soboczenski, Frank, Soman, Karthik, Van Valen, David, Venkateswaran, Kasthuri, Warren, Liz, Worthey, Liz, Yang, Jason H., Zitnik, Marinka, Costes, Sylvain V.

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Biological research and self-driving labs in deep space supported by artificial intelligence von Sanders, Lauren M., Scott, Ryan T., Yang, Jason H., Qutub, Amina Ann, Garcia Martin, Hector, Berrios, Daniel C., Hastings, Jaden J. A., Rask, Jon, Mackintosh, Graham, Hoarfrost, Adrienne L., Chalk, Stuart, Kalantari, John, Khezeli, Kia, Antonsen, Erik L., Babdor, Joel, Barker, Richard, Baranzini, Sergio E., Beheshti, Afshin, Delgado-Aparicio, Guillermo M., Glicksberg, Benjamin S., Greene, Casey S., Haendel, Melissa, Hamid, Arif A., Heller, Philip, Jamieson, Daniel, Jarvis, Katelyn J., Komarova, Svetlana V., Komorowski, Matthieu, Kothiyal, Prachi, Mahabal, Ashish, Manor, Uri, Mason, Christopher E., Matar, Mona, Mias, George I., Miller, Jack, Myers, Jerry G., Nelson, Charlotte, Oribello, Jonathan, Park, Seung-min, Parsons-Wingerter, Patricia, Prabhu, R. K., Reynolds, Robert J., Saravia-Butler, Amanda, Saria, Suchi, Sawyer, Aenor, Singh, Nitin Kumar, Snyder, Michael, Soboczenski, Frank, Soman, Karthik, Theriot, Corey A., Van Valen, David, Venkateswaran, Kasthuri, Warren, Liz, Worthey, Liz, Zitnik, Marinka, Costes, Sylvain V.

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Visualizing Magnitude: Graphical Number Representations Help Users Detect Large Number Entry Errors von Borghouts, Judith, Soboczenski, Frank, Cairns, Paul, Brumby, Duncan P.

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Question answering systems for health professionals at the point of care -- a systematic review von Kell, Gregory, Roberts, Angus, Umansky, Serge, Qian, Linglong, Ferrari, Davide, Soboczenski, Frank, Wallace, Byron, Patel, Nikhil, Marshall, Iain J

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On Invariance Penalties for Risk Minimization von Khezeli, Kia, Blaas, Arno, Soboczenski, Frank, Chia, Nicholas, Kalantari, John

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Next-Gen Machine Learning Supported Diagnostic Systems for Spacecraft von Vlontzos, Athanasios, Sutherland, Gabriel, Ganju, Siddha, Soboczenski, Frank

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Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document Summarization von Wallace, Byron C, Saha, Sayantan, Soboczenski, Frank, Marshall, Iain J

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Invariant Risk Minimisation for Cross-Organism Inference: Substituting Mouse Data for Human Data in Human Risk Factor Discovery von O'Donoghue, Odhran, Duckworth, Paul, Ughi, Giuseppe, Scheibenreif, Linus, Khezeli, Kia, Hoarfrost, Adrienne, Budd, Samuel, Foley, Patrick, Chia, Nicholas, Kalantari, John, Mackintosh, Graham, Soboczenski, Frank, Sanders, Lauren

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Accurate Machine Learning Atmospheric Retrieval via a Neural Network Surrogate Model for Radiative Transfer von Himes, Michael D, Harrington, Joseph, Cobb, Adam D, Baydin, Atilim Gunes, Soboczenski, Frank, O'Beirne, Molly D, Zorzan, Simone, Wright, David C, Scheffer, Zacchaeus, Domagal-Goldman, Shawn D, Arney, Giada N

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On Invariance Penalties for Risk Minimization von Khezeli, Kia, Blaas, Arno, Soboczenski, Frank, Chia, Nicholas, Kalantari, John

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Next-Gen Machine Learning Supported Diagnostic Systems for Spacecraft von Vlontzos, Athanasios, Sutherland, Gabriel, Ganju, Siddha, Soboczenski, Frank

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Question answering systems for health professionals at the point of care -- a systematic review von Kell, Gregory, Roberts, Angus, Umansky, Serge, Qian, Linglong, Ferrari, Davide, Soboczenski, Frank, Wallace, Byron, Patel, Nikhil, Marshall, Iain J

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