Rethinking Traditional Emergency Department Care Models in a Post-Coronavirus Disease-2019 World von Pourmand, Ali, Caggiula, Amy, Barnett, Jeremy, Ghassemi, Mateen, Shesser, Robert

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Characteristics of Patients Treated in ED "Hallway Beds" von Pourmand, Ali, Aljohani, Bandar, Shesser, Robert, Kane, Erin, Almulhim, Khalid, Ghassemi, Mateen, Chen, Chen, Alam, Salah

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Lack of Telemedicine Training in Academic Medicine: Are We Preparing the Next Generation? von Pourmand, Ali, Ghassemi, Mateen, Sumon, Kazi, Amini, Saeid B, Hood, Colton, Sikka, Neal

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Non-evidenced based treatment: An unintended cause of morbidity and mortality related to COVID-19 von Reihani, Hamidreza, Ghassemi, Mateen, Mazer-Amirshahi, Maryann, Aljohani, Bandar, Pourmand, Ali

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Shifting attention to an undervalued asset; the emergency department technician von Shesser, Robert, Ghassemi, Mateen, Sun, Emily, Keim, Amy, Marchak, Alex, Pourmand, Ali

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Hand Sanitizer Intoxication in the Emergency Department von Pourmand, Ali, Ghassemi, Mateen, Frasure, Sarah E, Kreisman, Alexandrer, Shesser, Robert

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Hand Sanitizer Intoxication in the Emergency Department von Pourmand, Ali, Ghassemi, Mateen, Frasure, Sarah E, Kreisman, Alexandrer, Shesser, Robert

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Tackling bias in AI health datasets through the STANDING Together initiative von Ganapathi, Shaswath, Palmer, Jo, Alderman, Joseph E., Calvert, Melanie, Espinoza, Cyrus, Gath, Jacqui, Ghassemi, Marzyeh, Heller, Katherine, Mckay, Francis, Karthikesalingam, Alan, Kuku, Stephanie, Mackintosh, Maxine, Manohar, Sinduja, Mateen, Bilal A., Matin, Rubeta, McCradden, Melissa, Oakden-Rayner, Lauren, Ordish, Johan, Pearson, Russell, Pfohl, Stephen R., Rostamzadeh, Negar, Sapey, Elizabeth, Sebire, Neil, Sounderajah, Viknesh, Summers, Charlotte, Treanor, Darren, Denniston, Alastair K., Liu, Xiaoxuan

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A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI von Sounderajah, Viknesh, Ashrafian, Hutan, Rose, Sherri, Shah, Nigam H., Ghassemi, Marzyeh, Golub, Robert, Kahn, Charles E., Esteva, Andre, Karthikesalingam, Alan, Mateen, Bilal, Webster, Dale, Milea, Dan, Ting, Daniel, Treanor, Darren, Cushnan, Dominic, King, Dominic, McPherson, Duncan, Glocker, Ben, Greaves, Felix, Harling, Leanne, Ordish, Johan, Cohen, Jérémie F., Deeks, Jon, Leeflang, Mariska, Diamond, Matthew, McInnes, Matthew D. F., McCradden, Melissa, Abràmoff, Michael D., Normahani, Pasha, Markar, Sheraz R., Chang, Stephanie, Liu, Xiaoxuan, Mallett, Susan, Shetty, Shravya, Denniston, Alastair, Collins, Gary S., Moher, David, Whiting, Penny, Bossuyt, Patrick M., Darzi, Ara

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The value of standards for health datasets in artificial intelligence-based applications von Arora, Anmol, Alderman, Joseph E., Palmer, Joanne, Ganapathi, Shaswath, Laws, Elinor, McCradden, Melissa D., Oakden-Rayner, Lauren, Pfohl, Stephen R., Ghassemi, Marzyeh, McKay, Francis, Treanor, Darren, Rostamzadeh, Negar, Mateen, Bilal, Gath, Jacqui, Adebajo, Adewole O., Kuku, Stephanie, Matin, Rubeta, Heller, Katherine, Sapey, Elizabeth, Sebire, Neil J., Cole-Lewis, Heather, Calvert, Melanie, Denniston, Alastair, Liu, Xiaoxuan

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TRIPOD+AI statement: Updated guidance for reporting clinical prediction models that use regression or machine learning methods von Collins, Gary S, Moons, Karel G.M, Dhiman, Paula, Riley, Richard D, Beam, Andrew L, Van Calster, Ben, Ghassemi, Marzyeh, Liu, Xiaoxuan, Reitsma, Johannes B, Van Smeden, Maarten, Boulesteix, Anne Laure, Camaradou, Jennifer Catherine, Celi, Leo Anthony, Denaxas, Spiros, Denniston, Alastair K, Glocker, Ben, Golub, Robert M, Harvey, Hugh, Heinze, Georg, Hoffman, Michael M, Kengne, André Pascal, Lam, Emily, Lee, Naomi, Loder, Elizabeth W, Maier-Hein, Lena, Mateen, Bilal A, McCradden, Melissa D, Oakden-Rayner, Lauren, Ordish, Johan, Parnell, Richard, Rose, Sherri, Singh, Karandeep, Wynants, Laure, Logullo, Patricia

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Revealing transparency gaps in publicly available COVID-19 datasets used for medical artificial intelligence development—a systematic review von Alderman, Joseph E, Charalambides, Maria, Sachdeva, Gagandeep, Laws, Elinor, Palmer, Joanne, Lee, Elsa, Menon, Vaishnavi, Malik, Qasim, Vadera, Sonam, Calvert, Melanie, Ghassemi, Marzyeh, McCradden, Melissa D, Ordish, Johan, Mateen, Bilal, Summers, Charlotte, Gath, Jacqui, Matin, Rubeta N, Denniston, Alastair K, Liu, Xiaoxuan

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Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations von Alderman, Joseph E, Palmer, Joanne, Laws, Elinor, McCradden, Melissa D, Ordish, Johan, Ghassemi, Marzyeh, Pfohl, Stephen R, Rostamzadeh, Negar, Cole-Lewis, Heather, Glocker, Ben, Calvert, Melanie, Pollard, Tom J, Gill, Jaspret, Gath, Jacqui, Adebajo, Adewale, Beng, Jude, Leung, Cassandra H, Kuku, Stephanie, Farmer, Lesley-Anne, Matin, Rubeta N, Mateen, Bilal A, McKay, Francis, Heller, Katherine, Karthikesalingam, Alan, Treanor, Darren, Mackintosh, Maxine, Oakden-Rayner, Lauren, Pearson, Russell, Manrai, Arjun K, Myles, Puja, Kumuthini, Judit, Kapacee, Zoher, Sebire, Neil J, Nazer, Lama H, Seah, Jarrel, Akbari, Ashley, Berman, Lew, Gichoya, Judy W, Righetto, Lorenzo, Samuel, Diana, Wasswa, William, Charalambides, Maria, Arora, Anmol, Pujari, Sameer, Summers, Charlotte, Sapey, Elizabeth, Wilkinson, Sharon, Thakker, Vishal, Denniston, Alastair, Liu, Xiaoxuan

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TRIPOD plus AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods von Collins, Gary S, Moons, Karel G.M, Dhiman, Paula, Riley, Richard, Beam, Andrew L, Van Calster, Ben, Ghassemi, Marzyeh, Liu, Xiaoxuan, Reitsma, Johannes B, van Smeden, Maarten, Boulesteix, Anne-Laure, Camaradou, Jennifer Catherine, Celi, Leo Anthony, Denaxas, Spiros, Denniston, Alastair K, Glocker, Ben, Golub, Robert M, Harvey, Hugh, Heinze, Georg, Hoffman, Michael M, Kengne, Andre Pascal, Lam, Emily, Lee, Naomi, Loder, Elizabeth W, Maier-Hein, Lena, Mateen, Bilal A, McCradden, Melissa, Oakden-Rayner, Lauren, Ordish, Johan, Parnell, Richard, Rose, Sherri, Singh, Karandeep, Wynants, Laure, Logullo, Patricia

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Revealing transparency gaps in publicly available COVID-19 datasets used for medical artificial intelligence development-a systematic review von Alderman, Joseph E, Charalambides, Maria, Sachdeva, Gagandeep, Laws, Elinor, Palmer, Joanne, Lee, Elsa, Menon, Vaishnavi, Malik, Qasim, Vadera, Sonam, Calvert, Melanie, Ghassemi, Marzyeh, McCradden, Melissa D, Ordish, Johan, Mateen, Bilal, Summers, Charlotte, Gath, Jacqui, Matin, Rubeta N, Denniston, Alastair K, Liu, Xiaoxuan

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The value of standards for health datasets in artificial intelligence-based applications von Arora, Anmol, Alderman, Joseph E, Palmer, Joanne, Ganapathi, Shaswath, Laws, Elinor, McCradden, Melissa D, Oakden-Rayner, Lauren, Pfohl, Stephen R, Ghassemi, Marzyeh, McKay, Francis, Treanor, Darren, Rostamzadeh, Negar, Mateen, Bilal, Gath, Jacqui, Adebajo, Adewole O, Kuku, Stephanie, Matin, Rubeta, Heller, Katherine, Sapey, Elizabeth, Sebire, Neil J, Cole-Lewis, Heather, Calvert, Melanie, Denniston, Alastair, Liu, Xiaoxuan

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The value of standards for health datasets in artificial intelligence-based applications von Arora, A, Alderman, JE, Palmer, J, Ganapathi, S, Laws, E, McCradden, MD, Oakden-Rayner, L, Pfohl, SR, Ghassemi, M, McKay, F, Treanor, D, Rostamzadeh, N, Mateen, B, Gath, J, Adebajo, AO, Kuku, S, Matin, R, Heller, K, Sapey, E, Sebire, NJ, Cole-Lewis, H, Calvert, M, Denniston, A, Liu, X

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TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods von Collins, Gary S, Moons, Karel GM, Dhiman, Paula, Riley, Richard D, Beam, Andrew L, Van Calster, Ben, Ghassemi, Marzyeh, Liu, Xiaoxuan, Reitsma, Johannes B, Van Smeden, Maarten, Boulesteix, Anne-Laure, Camaradou, Jennifer Catherine, Celi, Leo Anthony, Denaxas, Spiros, Denniston, Alastair K, Glocker, Ben, Golub, Robert M, Harvey, Hugh, Heinze, Georg, Hoffman, Michael M, Kengne, André Pascal, Lam, Emily, Lee, Naomi, Loder, Elizabeth W, Maier-Hein, Lena, Mateen, Bilal A, McCradden, Melissa D, Oakden-Rayner, Lauren, Ordish, Johan, Parnell, Richard, Rose, Sherri, Singh, Karandeep, Wynants, Laure, Logullo, Patricia

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TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods von Collins, Gary S, Moons, Karel G. M, Dhiman, Paula, Riley, Richard D, Beam, Andrew L, Calster, Ben van, Ghassemi, Marzyeh, Liu, Xiaoxuan, Reitsma, Johannes B, Smeden, Maarten van, Boulesteix, Anne-Laure, Camaradou, Jennifer Catherine, Celi, Leo Anthony, Denaxas, Spiros, Denniston, Alastair K, Glocker, Ben, Golub, Robert M, Harvey, Hugh, Heinze, Georg, Hoffman, Michael M, Kengne, André Pascal, Lam, Emily, Lee, Naomi, Loder, Elizabeth W, Maier-Hein, Lena, Mateen, Bilal A, McCradden, Melissa D, Oakden-Rayner, Lauren, Ordish, Johan, Parnell, Richard, Rose, Sherri, Singh, Karandeep, Wynants, Laure, Logullo, Patricia

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A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI von Sounderajah, V, Ashrafian, H, Rose, S, Shah, NH, Ghassemi, M, Golub, R, Kahn, CE, Esteva, A, Karthikesalingam, A, Mateen, B, Webster, D, Milea, D, Ting, D, Treanor, D, Cushnan, D, King, D, McPherson, D, Glocker, B, Greaves, F, Harling, L, Ordish, J, Cohen, JF, Deeks, J, Leeflang, M, Diamond, M, McInnes, MDF, McCradden, M, Abramoff, MD, Normahani, P, Markar, SR, Chang, S, Liu, X, Mallett, S, Shetty, S, Denniston, A, Collins, GS, Moher, D, Whiting, P, Bossuyt, PM, Darzi, A

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