Results 51 to 60 of about 1,444 (142)

Ensuring a safe(r) harbor: Excising personally identifiable information from structured electronic health record data

Journal of Clinical and Translational Science, 2022
Recent findings have shown that the continued expansion of the scope and scale of data collected in electronic health records are making the protection of personally identifiable information (PII) more challenging and may inadvertently put our ...
Emily R. Pfaff, Melissa A. Haendel, Kristin Kostka, Adam Lee, Emily Niehaus, Matvey B. Palchuk, Kellie Walters, Christopher G. Chute   +7 more
doaj   +1 more source

Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers

, 2015
The vision of creating accessible, reliable clinical evidence by accessing the clincial experience of hundreds of millions of patients across the globe is a reality. Observational Health Data Sciences and Informatics (OHDSI) has built on learnings from the Observational Medical Outcomes Partnership to turn methods research and insights into a suite of ...
Hripcsak, George, Duke, Jon D, Shah, Nigam H, Reich, Christian G, Huser, Vojtech, Schuemie, Martijn J, Suchard, Marc A, Park, Rae Woong, Wong, Ian Chi Kei, Rijnbeek, Peter R, van der Lei, Johan, Pratt, Nicole, Norén, G Niklas, Li, Yu-Chuan, Stang, Paul E, Madigan, David, Ryan, Patrick B   +16 more
openaire   +5 more sources

Accelerating real‐world prediction and research in Alzheimer's: The M3AD study

Alzheimer's &Dementia, Volume 22, Issue 3, March 2026.
Abstract Chronic diseases, including Alzheimer's disease (AD) and related dementia (ADRD), do not exist solely as isolated entities. Instead, they weave concomitant trajectories of multiple diseases, conditions, behaviors, and risks, mutually influencing each other's course and natural history, in ways yet unexplored.
Moïse Desvarieux, Tatjana Rundek, Habibul Ahsan, Javier Narvaez, Felipe Diaz, Daniel Malinsky, Luis Marco Ruiz, Maxim Topaz, Thomas Falconer, Karthik Natarajan, James Noble, Barbara Entwisle, Deepthi Puram, Tara Anand, Hsin Yi Chen, Xinzhuo Jiang, Yian Gu, Alan Cohen, Mary Beth Terry, Brandon Pierce, Howard Andrews, Emily Rogalsky, Shahla Farzana, George Gulotta, John Beard, Danielle Landron, Samuel L Volchenboum, Philippe Ravaud, Julie Johnson, Ezra Susser, Andrew Rundle, Ying Wei, Nick Tsinoremas, David Loewenstein, Linda Fried, Allison Aiello, Richard Mayeux, George Hripcsak   +37 more
wiley   +1 more source

Implementation of inclusion and exclusion criteria of clinical studies in the software OHDSI ATLAS

, 2023
Abstract Background Clinical trials are an essential part of the medical research process, but trials are often canceled due to lack of enrollment. Clinical trial recruitment support systems can help increase the number of participants by finding more suitable subjects.
Romina Blasini, Kornelia Marta Buchowicz, Henning Schneider, Birgit Samans, Keywan Sohrabi   +4 more
openaire   +1 more source

Integrating real‐world data with gold‐standard longitudinal clinical and genomic data to advance precision medicine for the Alzheimer's Disease Research Center Program and beyond: a proof‐of‐concept data platform

Alzheimer's &Dementia, Volume 22, Issue 3, March 2026.
Abstract INTRODUCTION Integrating real‐world data (RWD) with clinical research datasets creates more complete, context‐rich resources to drive discovery and enable precision medicine in Alzheimer's disease and related dementias. The National Alzheimer's Coordinating Center conducted a proof‐of‐concept (POC) project to link its longitudinal Uniform Data
Sarah Biber, Jessica E. Culhane, Maria G. Prado, Satish Mathew, Yohali Burrola‐Mendez, Imara I. West, Sarah Van Heiden, Jimmy Phuong, Shilpa Allimatti, Liam G. Lane, Krista L. Moulder, Brittany K. Hale, Amanda Kuzma, Li‐San Wang, Sujuan Gao, Albert Lai, Karthik Natarajan, Sophia Wang, John C. Morris, James M. Noble, Sean D. Mooney, Walter Kukull, Andrew J. Saykin, Kari A. Stephens   +23 more
wiley   +1 more source

Best Practices and Gaps in Current Regulatory and Health Technology Assessment Real‐World Evidence Policies for Medicines and Medical Devices: Current State of Play and Next Steps

Clinical and Translational Science, Volume 19, Issue 3, March 2026.
ABSTRACT Real‐world data (RWD) offers a valuable opportunity to access vast information that can drive research and generate real‐world evidence (RWE), offering insights into the actual delivery of care and patient outcomes beyond the limitations of traditional clinical trials.
Katharine Cresswell, Ravinder Claire, Laila Issa, Luke Kubehl, Omnia Bilal, Rose Purcell, Amaya Clemente, Jakob Wested, Lotte Groth Jensen, Medha Sasane, Rita Peeters, Bethany Shinkins, Heather Colvin   +12 more
wiley   +1 more source

Enhancing Severe Neutropenia Prediction: PKPD‐Informed Labeling for Machine Learning Models Trained on Real‐World Data

Clinical Pharmacology &Therapeutics, Volume 119, Issue 2, Page 427-436, February 2026.
Accurately labeling outcomes in real‐world data for machine learning is challenging due to data sparsity and imbalances. This study developed and evaluated a pharmacokinetic–pharmacodynamic (PKPD)‐informed labeling strategy to enhance the risk prediction of docetaxel‐induced neutropenia.
Conor J O’Hanlon, Jonas Denck, Elif Ozkirimli, Stefanie Bendels, Candice Jamois, Clarisse Chavanne, Dirk Fey, Kimmo Porkka, Oscar Brück, Ken Wang   +9 more
wiley   +1 more source

Medications Used Among Nonhospitalized Pregnant Women With COVID‐19: A Prospective Individual Patient Data Meta‐Analysis in Europe and North America

Pharmacoepidemiology and Drug Safety, Volume 35, Issue 1, January 2026.
ABSTRACT Aim To estimate the prevalence of medication use in nonhospitalized pregnant women with COVID‐19. Methods A prospective two‐stage individual patient meta‐analysis across 10 data sources in Europe and North America studied medication use among nonhospitalized pregnant women with COVID‐19 between January 2020 and December 2022.
Odette de Bruin, Emeline Maisonneuve, Eimir Hurley, Hedvig M. E. Nordeng, Anick Bérard, Odile Sheehy, Padma Kaul, Mayura U. Shinde, Austin Cosgrove, Jennifer G. Lyons, Elizabeth Messenger‐Jones, Maria E. Kempner, Sengwee Toh, Wei Hua, José J. Hernández‐Muñoz, Leyla Sahin, Carolyn E. Cesta, David Hägg, Rosa Gini, Olga Paoletti, Beatriz Poblador‐Plou, Sue Jordan, Daniel Thayer, Clara L. Rodríguez‐Bernal, Francisco Sánchez‐Sáez, Régis Lassalle, Marie‐Agnès Bernard, Ema Alsina, Fariba Ahmadizar, Guillaume Favre, Alice Panchaud, Kitty W. M. Bloemenkamp, Kelly Plueschke, Corinne de Vries, Satu J. Siiskonen, Miriam C. J. M. Sturkenboom, on behalf of the CONSIGN Collaboration Group, Benjamin P. Geisler, Mark Walker, Steven Hawken, Sasha Bernatsky, Sherif Eltonsy, Emma Hoffman, Andrew B. Petrone, Jolene Mosley, Jenice Ko, Claudia Bartolini, Giuseppe Roberto, Giorgio Limoncella, Anna Girardi, Giulia Hyeraci, Antonio Gimeno‐Miguel, Jonás Carmona‐Pírez, Antonio Poncel‐Falcó, Aida Moreno‐Juste, Alexandra Prados‐Torres, Ian Farr, Saira Ahmed, Ieuan Scanlon, Gabriel Sanfélix‐Gimeno, Isabel Hurtado, Anibal Garcia‐Sempere, Salvador Peiro, Jérémy Jové, Dunia Sakr, Cécile Droz‐Perroteau, David Baum, Hilde M. Engjom, Mònica Sabaté Gallego, Elena Ballarín Alins, Cristina Aguilera Martin, Melissa Kampman, Celline Brasil   +72 more
wiley   +1 more source

Development and validation of a prognostic model predicting symptomatic hemorrhagic transformation in acute ischemic stroke at scale in the OHDSI network.

PLoS ONE, 2020
Background and purposeHemorrhagic transformation (HT) after cerebral infarction is a complex and multifactorial phenomenon in the acute stage of ischemic stroke, and often results in a poor prognosis.
Qiong Wang, Jenna M Reps, Kristin Feeney Kostka, Patrick B Ryan, Yuhui Zou, Erica A Voss, Peter R Rijnbeek, RuiJun Chen, Gowtham A Rao, Henry Morgan Stewart, Andrew E Williams, Ross D Williams, Mui Van Zandt, Thomas Falconer, Margarita Fernandez-Chas, Rohit Vashisht, Stephen R Pfohl, Nigam H Shah, Suranga N Kasthurirathne, Seng Chan You, Qing Jiang, Christian Reich, Yi Zhou   +22 more
doaj   +1 more source

Physiological signal analysis and open science using the Julia language and associated software

Frontiers in Network Physiology
In this mini review, we propose the use of the Julia programming language and its software as a strong candidate for reproducible, efficient, and sustainable physiological signal analysis. First, we highlight available software and Julia communities that
George Datseris, Jacob S. Zelko, Jacob S. Zelko   +2 more
doaj   +1 more source