Countermeasure Analysis for Galactic Cosmic Radiation Induced Damage von Adams, Jessica, Haran, Harry, Nikisher, Bridgette, Edwards, John

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The Current Age of Medical Student Research: A Single-Institution Experience von Haran, Harry, Liddy, Nicole, Choe, Joshua, Nadler, Jerry L., Petzke, Mary M.

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The ethical considerations including inclusion and biases, data protection, and proper implementation among AI in radiology and potential implications von Martin, Clarissa, DeStefano, Kyle, Haran, Harry, Zink, Sydney, Dai, Jennifer, Ahmed, Danial, Razzak, Abrahim, Lin, Keldon, Kogler, Ann, Waller, Joseph, Kazmi, Khuram, Umair, Muhammad

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Control of protein activity by photoinduced spin polarized charge reorganization von Ghosh, Shirsendu, Banerjee-Ghosh, Koyel, Levy, Dorit, Scheerer, David, Riven, Inbal, Shin, Jieun, Gray, Harry B., Naaman, Ron, Haran, Gilad

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EHRA White Paper: knowledge gaps in arrhythmia management—status 2019 von Goette, Andreas, Auricchio, Angelo, Boriani, Giuseppe, Braunschweig, Frieder, Terradellas, Josep Brugada, Burri, Haran, Camm, A John, Crijns, Harry, Dagres, Nikolaos, Deharo, Jean-Claude, Dobrev, Dobromir, Hatala, Robert, Hindricks, Gerhard, Hohnloser, Stefan H, Leclercq, Christophe, Lewalter, Thorsten, Lip, Gregory Y H, Merino, Jose Luis, Mont, Lluis, Prinzen, Frits, Proclemer, Alessandro, Pürerfellner, Helmut, Savelieva, Irina, Schilling, Richard, Steffel, Jan, van Gelder, Isabelle C, Zeppenfeld, Katja, Zupan, Igor, Heidbüchel, Hein

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RecENT SHO (Rotating onto ear, nose and throat surgery): How well are new Senior House Officers prepared and supported? A UK‐wide multi‐centre survey von Gundle, Leo, Guest, Oscar, Hyland, Liam D., Khan, Atia, Grimes, Christian, Nunney, Ian, Tailor, Bhavesh V.

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Impact of the COVID‐19 pandemic on outcomes of cholecystectomy for acute cholecystitis: a national cohort study von Hua Liu, Gordon Xin, McGuinness, Matthew, Wells, Cameron I, Elliott, Brodie M, Gunawardene, Ashok, Edwards, Melissa, Wang, Jim Hsu‐Shun, Windsor, John, Ghate, Kaustubha, Lal, Shayal, Lekamalage, Binura, Ratnayake, Milidu, Windsor, John, Hemachandran, Arthana, Bhat, Sameer, Rossaak, Jeremy, Pan, Marcus, Ferguson, Liam, Watt, Imogen, Choi, Jenny, Mclauchlan, Jared, Connor, Saxon, Nicholas, Ella, Wood, Douglas, Bathgate, Andrea, Wehipeihana, Emma, Poole, Garth, Javed, Zunaira, Randall, Madi, Cook, William, Clark, Sita, Finlayson, Carys, Poole, Garth, Bahl, Praharsh, Singh, Surya, Lin, Cindy, Morreau, Mathew, Ing, Andrew, Guest, Sam, Lewis, Alex, Roberts, Jessica, Watson, Bridget, Tietjens, James, Teague, Rebecca, Su'a, Bruce, Modi, Anupam, Morreau, Jonty, Desmond, Brendan, Young, Michael, Harmston, Christopher, Barber, Lucy, Amer, Mostafa, Haddow, James, Amer, Mostafa, Fearnley‐Fitzgerald, Chekodi, Suresh, Karen, Zeng, Edwin, Young‐Gough, Anastasia, El‐Haddawi, Falah, Alvarez, Matias, Nguyen, Son, King, Jasmin, Crichton, James, Welsh, Fraser, Edwards, Melissa, Tan, Jeffrey, Luo, Jonathon, Banker, Karankumar, Field, Xavier, Srinivasa, Sanket, Singh, Nivedita, Kang, Grace, Srinivasa, Sanket, Cook, Holly, Mistry, Vyoma, Oca, Abraham Montes, Yoganandarajah, Vithushiya, Lill, Marianne, Lu, Jacky, Bonnet, Louis Antoine, Uiyapat, Thitapon, Spiers, Harry VM, Varghese, Chris, Griffiths, Ewen A, Poole, Garth H, Bissett, Ian P, Wright, Deborah, Kau, Niki, Hayes, Thomas, Have, Jelle, Scowcroft, Hannah, Mclauchlan, Jared, Jeffery, Fraser, Connor, Saxon, Varghese, Chris, Mashlan, Holly, Thirayan, Varun, Mcguinness, Matthew, Watt, Imogen, Harmston, Christopher

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Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies von Joel, Samantha, Eastwick, Paul W, Allison, Colleen J, Arriaga, Ximena B, Baker, Zachary G, Bar-Kalifa, Eran, Bergeron, Sophie, Birnbaum, Gurit E, Brock, Rebecca L, Brumbaugh, Claudia C, Carmichael, Cheryl L, Chen, Serena, Clarke, Jennifer, Cobb, Rebecca J, Coolsen, Michael K, Davis, Jody, de Jong, David C, Debrot, Anik, DeHaas, Eva C, Derrick, Jaye L, Eller, Jami, Estrada, Marie-Joelle, Faure, Ruddy, Finkel, Eli J, Fraley, R Chris, Gable, Shelly L, Gadassi-Polack, Reuma, Girme, Yuthika U, Gordon, Amie M, Gosnell, Courtney L, Hammond, Matthew D, Hannon, Peggy A, Harasymchuk, Cheryl, Hofmann, Wilhelm, Horn, Andrea B, Impett, Emily A, Jamieson, Jeremy P, Keltner, Dacher, Kim, James J, Kirchner, Jeffrey L, Kluwer, Esther S, Kumashiro, Madoka, Larson, Grace, Lazarus, Gal, Logan, Jill M, Luchies, Laura B, MacDonald, Geoff, Machia, Laura V, Maniaci, Michael R, Maxwell, Jessica A, Mizrahi, Moran, Muise, Amy, Niehuis, Sylvia, Ogolsky, Brian G, Oldham, C Rebecca, Overall, Nickola C, Perrez, Meinrad, Peters, Brett J, Pietromonaco, Paula R, Powers, Sally I, Prok, Thery, Pshedetzky-Shochat, Rony, Rafaeli, Eshkol, Ramsdell, Erin L, Reblin, Maija, Reicherts, Michael, Reifman, Alan, Reis, Harry T, Rhoades, Galena K, Rholes, William S, Righetti, Francesca, Rodriguez, Lindsey M, Rogge, Ron, Rosen, Natalie O, Saxbe, Darby, Sened, Haran, Simpson, Jeffry A, Slotter, Erica B, Stanley, Scott M, Stocker, Shevaun, Surra, Cathy, Ter Kuile, Hagar, Vaughn, Allison A, Vicary, Amanda M, Visserman, Mariko L, Wolf, Scott

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A relational database design in support of standard medical terminology in multi-domain knowledge bases von Naeymi-Rad, Frank, Carmony, Lowell, Trace, David, Georgakis, Christine, Weil, Max Harry

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