The role of machine learning in clinical research: transforming the future of evidence generation

EH Weissler, T Naumann, T Andersson, R Ranganath… - Trials, 2021 - Springer
Background Interest in the application of machine learning (ML) to the design, conduct, and
analysis of clinical trials has grown, but the evidence base for such applications has not …

Text mining for adverse drug events: the promise, challenges, and state of the art

R Harpaz, A Callahan, S Tamang, Y Low, D Odgers… - Drug safety, 2014 - Springer
Text mining is the computational process of extracting meaningful information from large
amounts of unstructured text. It is emerging as a tool to leverage underutilized data sources …

A curated and standardized adverse drug event resource to accelerate drug safety research

JM Banda, L Evans, RS Vanguri, NP Tatonetti… - Scientific data, 2016 - nature.com
Identification of adverse drug reactions (ADRs) during the post-marketing phase is one of
the most important goals of drug safety surveillance. Spontaneous reporting systems (SRS) …

[HTML][HTML] Using electronic health records for clinical research: the case of the EHR4CR project

G De Moor, M Sundgren, D Kalra, A Schmidt… - Journal of biomedical …, 2015 - Elsevier
Objectives To describe the IMI EHR4CR project which is designing and develo**, and
aims to demonstrate, a scalable, widely acceptable and efficient approach to interoperability …

Good signal detection practices: evidence from IMI PROTECT

AFZ Wisniewski, A Bate, C Bousquet, A Brueckner… - Drug safety, 2016 - Springer
Over a period of 5 years, the Innovative Medicines Initiative PROTECT (
Pharmacoepidemiological Research on Outcomes of Therapeutics by a European …

Risk of lower extremity amputations in people with type 2 diabetes mellitus treated with sodium‐glucose co‐transporter‐2 inhibitors in the USA: a retrospective cohort …

Z Yuan, FJ DeFalco, PB Ryan… - Diabetes, Obesity …, 2018 - Wiley Online Library
Aims To examine the incidence of amputation in patients with type 2 diabetes mellitus
(T2DM) treated with sodium glucose co‐transporter 2 (SGLT2) inhibitors overall, and …

Desiderata for computable representations of electronic health records-driven phenotype algorithms

H Mo, WK Thompson, LV Rasmussen… - Journal of the …, 2015 - academic.oup.com
Abstract Background Electronic health records (EHRs) are increasingly used for clinical and
translational research through the creation of phenotype algorithms. Currently, phenotype …

[HTML][HTML] Accuracy of an automated knowledge base for identifying drug adverse reactions

EA Voss, RD Boyce, PB Ryan, J van der Lei… - Journal of biomedical …, 2017 - Elsevier
Introduction Drug safety researchers seek to know the degree of certainty with which a
particular drug is associated with an adverse drug reaction. There are different sources of …

[HTML][HTML] Incidence of diabetic ketoacidosis among patients with type 2 diabetes mellitus treated with SGLT2 inhibitors and other antihyperglycemic agents

Y Wang, M Desai, PB Ryan, FJ DeFalco… - Diabetes research and …, 2017 - Elsevier
Aims To estimate and compare incidence of diabetes ketoacidosis (DKA) among patients
with type 2 diabetes who are newly treated with SGLT2 inhibitors (SGLT2i) versus non …

Representing knowledge consistently across health systems

ST Rosenbloom, RJ Carroll, JL Warner… - Yearbook of medical …, 2017 - thieme-connect.com
Objectives: Electronic health records (EHRs) have increasingly emerged as a powerful
source of clinical data that can be leveraged for reuse in research and in modular health …