Publications using ARCH data

Bhambhvani HP, Rodrigues AJ, Yu JS, Carr JB, Hayden Gephart M. Hospital volumes of 5 medical emergencies in the COVID-19 pandemic in 2 US Medical Centers. JAMA Internal Medicine. 2021;181(2):272. 

Brar G, Pinheiro LC, Shusterman M, Swed B, Reshetnyak E, Soroka O, et al. Covid-19 severity and outcomes in patients with cancer: A matched cohort study. Journal of Clinical Oncology. 2020;38(33):3914–24. 

Choi JJ, Wehmeyer GT, Li HA, Alshak MN, Nahid M, Rajan M, et al. D-dimer cut-off points and risk of venous thromboembolism in adult hospitalized patients with COVID-19. Thrombosis Research. 2020;196:318–21. 

Hajifathalian K, Sharaiha RZ, Kumar S, Krisko T, Skaf D, Ang B, et al. Development and external validation of a prediction risk model for short-term mortality among hospitalized U.S. COVID-19 patients: A proposal for the COVID-aid risk tool. PLOS ONE. 2020;15(9). 

Khan R, Sholle E, Razavi A, Gelber SE. Predictive cutoffs of 1-hour GCT prior to 16 weeks in diagnosing carbohydrate intolerance in early gestation [36l]. Obstetrics & Gynecology. 2018;131(1). 

Lee JR, Silberzweig J, Akchurin O, Choi ME, Srivatana V, Lin J, et al. Characteristics of acute kidney injury in hospitalized COVID-19 patients in an urban academic medical center. Clinical Journal of the American Society of Nephrology. 2020;16(2):284–6.  

Shah MA, Mayer S, Emlen F, Sholle E, Christos P, Cushing M, et al. Clinical screening for COVID-19 in asymptomatic patients with cancer. JAMA Network Open. 2020;3(9). 

Sholle E, Krichevsky S, Scandura J, Sosner C, Campion T. Lessons learned in the development of a computable phenotype for response in myeloproliferative neoplasms. 2018 IEEE International Conference on Healthcare Informatics (ICHI). 2018; 

Sholle E, Krichevsky S, Scandura J, Sosner C, Savage N, Campion TR. Development of an automated tool for assessing response in patients with Polycythemia Vera. Blood. 2018;132(Supplement 1):5462–. 

Singh G, Hussain Y, Xu Z, Sholle E, Michalak K, Dolan K, et al. Comparing a novel machine learning method to the Friedewald formula and Martin-Hopkins equation for low-density lipoprotein estimation. PLOS ONE. 2020;15(9).  

Zhang Y, Tayarani M, Al’Aref SJ, Beecy AN, Liu Y, Sholle E, et al. Using electronic health records for Population Health Sciences: A case study to evaluate the associations between changes in left ventricular ejection fraction and the built environment. JAMIA Open. 2020;3(3):386–94. 

Zhang Y, Wang S, Hermann A, Joly R, Pathak J. Development and validation of a machine learning algorithm for predicting the risk of postpartum depression among pregnant women. Journal of Affective Disorders. 2021;279:1–8. 

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