Search Results - "Gouripeddi, Ramkiran"

STHAM: an agent based model for simulating human exposure across high resolution spatiotemporal domains by Lund, Albert M., Gouripeddi, Ramkiran, Facelli, Julio C.

“…Human exposure to particulate matter and other environmental species is difficult to estimate in large populations. Individuals can encounter significant and…”
Get full text

Clinical Characterization and Prediction of Clinical Severity of SARS-CoV-2 Infection Among US Adults Using Data From the US National COVID Cohort Collaborative by Bennett, Tellen D, Moffitt, Richard A, Hajagos, Janos G, Amor, Benjamin, Anand, Adit, Bissell, Mark M, Bradwell, Katie Rebecca, Bremer, Carolyn, Byrd, James Brian, Denham, Alina, DeWitt, Peter E, Gabriel, Davera, Garibaldi, Brian T, Girvin, Andrew T, Guinney, Justin, Hill, Elaine L, Hong, Stephanie S, Jimenez, Hunter, Kavuluru, Ramakanth, Kostka, Kristin, Lehmann, Harold P, Levitt, Eli, Mallipattu, Sandeep K, Manna, Amin, McMurry, Julie A, Morris, Michele, Muschelli, John, Neumann, Andrew J, Palchuk, Matvey B, Pfaff, Emily R, Qian, Zhenglong, Qureshi, Nabeel, Russell, Seth, Spratt, Heidi, Walden, Anita, Williams, Andrew E, Wooldridge, Jacob T, Yoo, Yun Jae, Zhang, Xiaohan Tanner, Zhu, Richard L, Austin, Christopher P, Saltz, Joel H, Gersing, Ken R, Haendel, Melissa A, Chute, Christopher G

“…The National COVID Cohort Collaborative (N3C) is a centralized, harmonized, high-granularity electronic health record repository that is the largest, most…”
Get full text

Human activity pattern implications for modeling SARS-CoV-2 transmission by Wang, Yulan, Li, Bernard, Gouripeddi, Ramkiran, Facelli, Julio C.

“…•Human activity patterns are important in predicting the rate of infection for different demographic groups in the population and future work in pandemic…”
Get full text

Detecting hypoglycemia-induced electrocardiogram changes in a rodent model of type 1 diabetes using shape-based clustering by Mistry, Sejal, Gouripeddi, Ramkiran, Reno, Candace M, Abdelrahman, Samir, Fisher, Simon J, Facelli, Julio C

“…Sudden death related to hypoglycemia is thought to be due to cardiac arrhythmias. A clearer understanding of the cardiac changes associated with hypoglycemia…”
Get full text

Travel Distance Between Participants in US Telemedicine Sessions With Estimates of Emissions Savings: Observational Study by Cummins, Mollie R, Shishupal, Sukrut, Wong, Bob, Wan, Neng, Han, Jiuying, Johnny, Jace D, Mhatre-Owens, Amy, Gouripeddi, Ramkiran, Ivanova, Julia, Ong, Triton, Soni, Hiral, Barrera, Janelle, Wilczewski, Hattie, Welch, Brandon M, Bunnell, Brian E

“…Digital health and telemedicine are potentially important strategies to decrease health care's environmental impact and contribution to climate change by…”
Get full text

297 Identifying Opportunities and Challenges for Translational Informatics Approaches to Real-World Data: A Diabetes Case Study by Mistry, Sejal, Gouripeddi, Ramkiran, Facelli, Julio C.

“…OBJECTIVES/GOALS: Diabetes is a group of chronic metabolic diseases and significant gaps remain in our understanding of disease etiology, treatment regimens,…”
Get full text

73432 Assessment of multi-pollutant ambient air composition on type 2 diabetes mellitus using machine learning by Riches, Naomi Oiwa, Gouripeddi, Ramkiran, Facelli, Julio C.

“…ABSTRACT IMPACT: We explored the use of machine learning to explore how multi-pollutant air quality is related to type 2 diabetes, which is more representative…”
Get full text

27337 Characterizing Temporal Patterns in Glucose Dysregulation Following SARS-CoV-2 Infection by Mistry, Sejal, Gouripeddi, Ramkiran, Facelli, Julio C.

“…ABSTRACT IMPACT: Understanding the longitudinal glucose changes following SARS-CoV-2 infection can inform point-of-care guidelines and elucidate the viral…”
Get full text

Information Extraction From Electronic Health Records to Predict Readmission Following Acute Myocardial Infarction: Does Natural Language Processing Using Clinical Notes Improve Prediction of Readmission? by Brown, Jeremiah R, Ricket, Iben M, Reeves, Ruth M, Shah, Rashmee U, Goodrich, Christine A, Gobbel, Glen, Stabler, Meagan E, Perkins, Amy M, Minter, Freneka, Cox, Kevin C, Dorn, Chad, Denton, Jason, Bray, Bruce E, Gouripeddi, Ramkiran, Higgins, John, Chapman, Wendy W, MacKenzie, Todd, Matheny, Michael E

“…Background Social risk factors influence rehospitalization rates yet are challenging to incorporate into prediction models. Integration of social risk factors…”
Get full text

Towards a Newborn Screening Common Data Model: The Utah Newborn Screening Data Model by Jones, David, Shao, Jianyin, Wallis, Heidi, Johansen, Cody, Hart, Kim, Pasquali, Marzia, Gouripeddi, Ramkiran, Rohrwasser, Andreas

“…As newborn screening programs transition from paper-based data exchange toward automated, electronic methods, significant data exchange challenges must be…”
Get full text

A survey of practices for the use of electronic health records to support research recruitment by Obeid, Jihad S, Beskow, Laura M, Rape, Marie, Gouripeddi, Ramkiran, Black, R Anthony, Cimino, James J, Embi, Peter J, Weng, Chunhua, Marnocha, Rebecca, Buse, John B

“…Electronic health records (EHRs) provide great promise for identifying cohorts and enhancing research recruitment. Such approaches are sorely needed, but there…”
Get full text

Healthcare Provider Reports on Social Determinants of Health in Opioid Treatment by Cambron, Christopher, Gouripeddi, Ramkiran, Facelli, Julio C.

“…Opioid overdose and death from overdose continue to present a pressing problem in the United States. It is well-established that a range of social and economic…”
Get full text

Prioritization of infectious epitopes for translational investigation in type 1 diabetes etiology by Mistry, Sejal, Gouripeddi, Ramkiran, Facelli, Julio C.

“…Molecular mimicry is one mechanism by which infectious agents are thought to trigger islet autoimmunity in type 1 diabetes. With a growing number of reported…”
Get full text

Stratifying risk for onset of type 1 diabetes using islet autoantibody trajectory clustering by Mistry, Sejal, Gouripeddi, Ramkiran, Raman, Vandana, Facelli, Julio C.

“…Aims/hypothesis Islet autoantibodies can be detected prior to the onset of type 1 diabetes and are important tools for aetiologic studies, prevention trials…”
Get full text

Abstract 17253: Concepts Associated With 30-day Rehospitalization From Unstructured Data Among Patients With Heart Failure by Kang, Youjeong, Stewart, Caden, Stehlik, Josef, Shen, Jincheng, Gouripeddi, Ramkiran, Sideris, Konstantinos, Facelli, Julio

“…Abstract only Introduction: Heart failure (HF) is a diagnosis for which the Centers for Medicare & Medicaid Services mandated public reporting on 30-day…”
Get full text

Sequential data mining of infection patterns as predictors for onset of type 1 diabetes in genetically at-risk individuals by Mistry, Sejal, Gouripeddi, Ramkiran, Raman, Vandana, Facelli, Julio C.

“…[Display omitted] Infections are implicated in the etiology of type 1 diabetes mellitus (T1DM); however, conflicting epidemiologic evidence makes designing…”
Get full text

Environmental exposures in machine learning and data mining approaches to diabetes etiology: A scoping review by Mistry, Sejal, Riches, Naomi O., Gouripeddi, Ramkiran, Facelli, Julio C.

“…Environmental exposures are implicated in diabetes etiology, but are poorly understood due to disease heterogeneity, complexity of exposures, and analytical…”
Get full text

K-means cluster analysis of cooperative effects of CO, NO2, O3, PM2.5, PM10, and SO2 on incidence of type 2 diabetes mellitus in the US by Riches, Naomi O., Gouripeddi, Ramkiran, Payan-Medina, Adriana, Facelli, Julio C.

“…Air pollution (AP) has been shown to increase the risk of type 2 diabetes mellitus, as well as other cardiometabolic diseases. AP is characterized by a complex…”
Get full text

Erratum to: Data-driven identification of temporal glucose patterns in a large cohort of nondiabetic patients with COVID-19 using time-series clustering by Mistry, Sejal, Gouripeddi, Ramkiran, Facelli, Julio C

Get full text

EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites by Nelson, Sarah J, Drury, Bethany, Hood, Daniel, Harper, Jeremy, Bernard, Tiffany, Weng, Chunhua, Kennedy, Nan, LaSalle, Bernie, Gouripeddi, Ramkiran, Wilkins, Consuelo H, Harris, Paul

“…Abstract Objective The Recruitment Innovation Center (RIC), partnering with the Trial Innovation Network and institutions in the National Institutes of…”
Get full text