Effect of systemic penicillin on pain in untreated irreversible pulpitis von Nagle, Douglas, Reader, Al, Beck, Mike, Weaver, Joel

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Myocardial surgical revascularization after streptokinase treatment for acute myocardial infarction von Losman, JG, Finchum, RN, Nagle, D, Dacumos, GC, Jones, CR, Wilensky, AS, Martin, RG, Bailey, MT, Kahn, DR

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Overview of Therapeutic Ultrasound Applications and Safety Considerations von Miller, Douglas L., Smith, Nadine B., Bailey, Michael R., Czarnota, Gregory J., Hynynen, Kullervo, Makin, Inder Raj S.

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Passive biomechanical properties of human cadaveric levator ani muscle at low strains von Nagle, Anna S, Barker, Matthew A, Kleeman, Steven D, Haridas, Balakrishna, Douglas Mast, T

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Using Machine Learning (XGBoost) to Predict Outcomes After Infrainguinal Bypass for Peripheral Artery Disease von Li, Ben, Eisenberg, Naomi, Beaton, Derek, Lee, Douglas S, Aljabri, Badr, Verma, Raj, Wijeysundera, Duminda N, Rotstein, Ori D, de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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Using machine learning to predict outcomes following carotid endarterectomy von Li, Ben, Beaton, Derek, Eisenberg, Naomi, Lee, Douglas S., Wijeysundera, Duminda N., Lindsay, Thomas F., de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting von Li, Ben, Eisenberg, Naomi, Beaton, Derek, Lee, Douglas S, Al-Omran, Leen, Wijeysundera, Duminda N, Hussain, Mohamad A, Rotstein, Ori D, de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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Clinical impact of COVID-19 on patients with cancer (CCC19): a cohort study von Choueiri, Toni K, Shyr, Yu, Grivas, Petros, Thompson, Michael A, Bilen, Mehmet A, Bouganim, Nathaniel, Doroshow, Deborah B, Egan, Pamela C, Elkrief, Arielle, Farmakiotis, Dimitrios, Glover, Michael J, Griffiths, Elizabeth A, Gulati, Anthony P, Gupta, Shilpa, Hsu, Emily, Lemmon, Christopher A, Lewis, Colleen, Masters, Tyler, Mesa, Ruben A, Morgans, Alicia K, Reynolds, Kerry, Rosen, Lane R, Schmidt, Andrew, Shaya, Justin A, Wulff-Burchfield, Elizabeth, Xie, Zhuoer, Yu, Peter P, Zubiri, Leyre, Warner, Jeremy L, Acoba, Jared D., Agarwal, Neeraj, Ahmad, Syed, Ajmera, Archana, Angevine, Anne H., Azad, Nilo, Barnholtz-Sloan, Jill, Barrow, Briana, Boland, Genevieve, Bonnen, Mark, Bouchard, Gabrielle, Busser, Fiona, Casulo, Carla, Curran, Catherine, Deeken, John, Demetri, George D., DiLullo, Sandy, Elias, Rawad, Feldman, Lawrence E., Friese, Christopher R., Fu, Paul, Gillaspie, Erin A., Giordano, Antonio, Glace, (Mary) Grace, Gurley, Michael, Halmos, Balazs, Johnson, Douglas B., Koshkin, Vadim S., Leighton, John C., Li, Xuanyi, LoRusso, Patricia, Low, Clarke A., Mansoor, Abdul-Hai, Handy Marshall, Catherine, Matar, Sara, McNair, Christopher, Mehnert, Janice M., Menon, Harry, Nagle, Sarah, Nakayama, John M., Nelson, Heather H., Nemecek, Eneida R., Nuzzo, Pier Vitale, Oberstein, Paul E., Owenby, Susie, Pasquinelli, Mary M., Revankar, Sanjay G., Rho, Young Soo, Rhodes, Terence D., Rice, Robert L., Riess, Jonathan, Routy, Bertrand, Rovito, Marc A., Saif, M. Wasif, Sanyal, Amit, Serrano, Oscar, Shah, Mansi, Shaw, Grace, Shergill, Ardaman, Stauffer, Karen, Stratton, Jamie, Stratton, Catherine, Subbiah, Vivek, Tannir, Nizar M., Van Allen, Eli, Verma, Amit K., Vikas, Praveen, Weiss, Matthias, Wise-Draper, Trisha, Wood, William A., Zacks, Rosemary

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Using machine learning to predict outcomes following suprainguinal bypass von Li, Ben, Eisenberg, Naomi, Beaton, Derek, Lee, Douglas S., Aljabri, Badr, Wijeysundera, Duminda N., Rotstein, Ori D., de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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Analysis of tissue changes, measurement system effects, and motion artifacts in echo decorrelation imaging von Hooi, Fong Ming, Nagle, Anna, Subramanian, Swetha, Douglas Mast, T

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Using machine learning to predict outcomes following open abdominal aortic aneurysm repair von Li, Ben, Aljabri, Badr, Verma, Raj, Beaton, Derek, Eisenberg, Naomi, Lee, Douglas S., Wijeysundera, Duminda N., Forbes, Thomas L., Rotstein, Ori D., de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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Lysophosphatidic acid activates peroxisome proliferator activated receptor-γ in CHO cells that over-express glycerol 3-phosphate acyltransferase-1 von Stapleton, Cliona M, Mashek, Douglas G, Wang, Shuli, Nagle, Cynthia A, Cline, Gary W, Thuillier, Philippe, Leesnitzer, Lisa M, Li, Lei O, Stimmel, Julie B, Shulman, Gerald I, Coleman, Rosalind A

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Machine learning to predict outcomes following endovascular abdominal aortic aneurysm repair von Li, Ben, Aljabri, Badr, Verma, Raj, Beaton, Derek, Eisenberg, Naomi, Lee, Douglas S, Wijeysundera, Duminda N, Forbes, Thomas L, Rotstein, Ori D, de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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Comparison of Transcriptomic Platforms for Analysis of Whole Blood from Ebola-Infected Cynomolgus Macaques von Speranza, Emily, Altamura, Louis A., Kulcsar, Kirsten, Bixler, Sandra L., Rossi, Cynthia A., Schoepp, Randal J., Nagle, Elyse, Aguilar, William, Douglas, Christina E., Delp, Korey L., Minogue, Timothy D., Palacios, Gustavo, Goff, Arthur J., Connor, John H.

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Using Machine Learning to Predict Outcomes Following Carotid Artery Stenting von Li, Ben, Aljabri, Badr, Beaton, Derek, Hussain, Mohamad A., Lee, Douglas S., Wijeysundera, Duminda N., Rotstein, Ori D., de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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Using Machine Learning to Predict Outcomes Following Thoracic and Complex Endovascular Aortic Aneurysm Repair von Li, Ben, Eisenberg, Naomi, Beaton, Derek, Lee, Douglas S., Aljabri, Badr, Al-Omran, Leen, Wijeysundera, Duminda N., Rotstein, Ori D., Lindsay, Thomas F., de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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Using machine learning to predict outcomes following carotid endarterectomy von Li, Ben, Beaton, Derek, Eisenberg, Naomi, Lee, Douglas S., Wijeysundera, Duminda N., Lindsay, Thomas F., de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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Using Machine Learning (XGBoost) to Predict Outcomes following Infrainguinal Bypass for Peripheral Artery Disease von Li, Ben, Eisenberg, Naomi, Beaton, Derek, Lee, Douglas S., Aljabri, Badr, Verma, Raj, Wijeysundera, Duminda N., Rotstein, Ori D., de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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The Contemporary Natural History of Medically Managed Asymptomatic Carotid Artery Stenosis von Husein, Adnan, Law, Daniel, Al-Omran, Mohammed, Lee, Douglas S., Roche-Nagle, Graham, Eisenberg, Naomi, Everett, Karl, Austin, Peter C., de Mestral, Charles

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Predicting lack of clinical improvement following varicose vein ablation using machine learning von Li, Ben, Eisenberg, Naomi, Beaton, Derek, Lee, Douglas S., Al-Omran, Leen, Wijeysundera, Duminda N., Hussain, Mohamad A., Rotstein, Ori D., de Mestral, Charles, Mamdani, Muhammad, Roche-Nagle, Graham, Al-Omran, Mohammed

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