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Wagner, Tyler

https://orcid.org/0000-0003-1726-016X

Mayo Clinic

DNA Medicine Institute (United States)

Citations 13

An Automated Screening Algorithm Using Electrocardiograms for Pulmonary Hypertension
Wagner, Tyler , Asirvatham, S, Babu, Mittapalli Jeevan, Barve, Rakesh , Carlson, Katherine , Carpenter, Corinne , Friedman, Paul A. , Prasad, A., Chehoud, C., Kogan, E., Nnewihe, A., Quinn, D., Bridges, C., Soundararajan, V., DuBrock, Hilary M. , Wagner, T., Attia, Zachi I. , Awasthi, Samir , Frantz, Robert P. , Kogan, E. I. , Kapa, Suraj

D3. D003 COME TOGETHER - CLINICAL ADVANCES IN PULMONARY HYPERTENSION: LESSONS FROM BEST ABSTRACTS | May 4, 2021 | Volume: No volume available | Issue: No issue available | Pages: A1179-A1179

10.1164/ajrccm-conference.2021.203.1_meetingabstracts.a1179 Get It

Author response: Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis
Wagner, Tyler , Bade, Sairam, Puranik, Arjun, Kang, Martin , Pickering, Brian W. , Temesgen, Zelalem , Rizza, Stacey A. , Wilson, Walter R. , Liebers, Matt, Doctor, Zainab M., Silvert, Eli , Solomon, Hugo, Barve, Rakesh , Williams, Amy W. , Morice, William G. , Wagner, Tyler, Shweta, Fnu , Murugadoss, Karthik , Awasthi, Samir , Venkatakrishnan, A J , O’Horo, John C. , Bauer, Philippe R. , Razonable, Raymund R. , Vergidis, Paschalis , Mahmood, Maryam , Challener, Douglas W. , Anand, Praveen , Anand, Akash, Gores, Gregory J. , Morice, William George , Halamka, John , Badley, Andrew D. , Soundararajan, Venky

No container title available | August 6, 2020 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.7554/elife.58227.sa2 Get It

Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis
Wagner, Tyler , Shweta, Fnu , Awasthi, Samir , Bade, Sairam, Puranik, Arjun, Kang, Martin , Pickering, Brian W. , O’Horo, John C. , Vergidis, Paschalis , Temesgen, Zelalem , Rizza, Stacey A. , Mahmood, Maryam , Wilson, Walter R. , Liebers, Matt, Doctor, Zainab M., Silvert, Eli , Solomon, Hugo, Barve, Rakesh , Williams, Amy W. , Morice, William G. , Badley, Andrew D. , Venkatakrishnan, A J , O'Horo, John C, Rizza, Stacey , Challener, Douglas , Anand, Praveen , Badley, Andrew, Soundararajan, Venky , Badley, Andrew D , O'Horo, John C , Vergidis, Paschalis , Mahmood, Maryam , Shweta, Fnu , Wagner, Tyler, Murugadoss, Karthik , Bauer, Philippe R. , Razonable, Raymund R. , Challener, Douglas W. , Anand, Praveen , Anand, Akash, Gores, Gregory J. , Morice, William George , Halamka, John , Soundararajan, Venky

eLife | July 7, 2020 | Volume: 9 | Issue: No issue available | Pages: No page available

10.7554/elife.58227 Get It

Understanding temporal dynamics of COVID-19 symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVID pos ; n = 2,317) versus COVID-19-negative (COVID neg ; n = 74,850) patients for the week preceding the PCR testing date, we identify anosmia/dysgeusia (27.1-fold), fever/chills (2.6-fold), respiratory difficulty (2.2-fold), cough (2.2-fold), myalgia/arthralgia (2-fold), and diarrhea (1.4-fold) as significantly amplified in COVID pos over COVID neg patients. The combination of cough and fever/chills has 4.2-fold amplification in COVID pos patients during the week prior to PCR testing, in addition to anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.