Results 81 to 90 of about 1,576 (169)

An AI‐first framework for multimodal data in Alzheimer's disease and related dementias

Alzheimer's &Dementia, Volume 21, Issue 9, September 2025.
Abstract Advancing the understanding and management of Alzheimer's disease and related dementias requires integrating and analyzing diverse data modalities. Traditional diagnostic tools, like neuroimaging, provide valuable insights but are limited by accessibility and infrastructure demands.
Varuna H. Jasodanand, Matteo Bellitti, Vijaya B. Kolachalama   +2 more
wiley   +1 more source

10 Practical Considerations for the Conduct of Multi‐National/Database Studies in Pharmacoepidemiology

Pharmacoepidemiology and Drug Safety, Volume 34, Issue 9, September 2025.
ABSTRACT Background Multi‐national/database pharmacoepidemiological studies are increasingly used to address questions that require pooled evidence across populations but introduce challenges in design, harmonization, and analysis. Objective To share 10 practical considerations and common pitfalls in planning, executing, and reporting multi‐national ...
Kenneth K. C. Man, Anton Pottegård
wiley   +1 more source

The OMOP common data model in Australian primary care data: Building a quality research ready harmonised dataset.

PLoS ONE
BackgroundThe use of routinely collected health data for secondary research purposes is increasingly recognised as a methodology that advances medical research, improves patient outcomes, and guides policy.
Roger Ward, Christine Mary Hallinan, David Ormiston-Smith, Christine Chidgey, Dougie Boyle   +4 more
doaj   +1 more source

Developing a portable natural language processing based phenotyping system

BMC Medical Informatics and Decision Making, 2019
Background This paper presents a portable phenotyping system that is capable of integrating both rule-based and statistical machine learning based approaches.
Himanshu Sharma, Chengsheng Mao, Yizhen Zhang, Haleh Vatani, Liang Yao, Yizhen Zhong, Luke Rasmussen, Guoqian Jiang, Jyotishman Pathak, Yuan Luo   +9 more
doaj   +1 more source

A study on the utilization of canagliflozin in type 1 diabetes mellitus using real‐world data from four European countries

Diabetes, Obesity and Metabolism, Volume 27, Issue 9, Page 5217-5224, September 2025.
Abstract Aims Sodium‐glucose co‐transporter‐2 (SGLT2) inhibitors are not approved for glycaemic control in type 1 diabetes mellitus (T1DM), and concerns exist around off‐label use in this patient population. The objective of this study was to investigate whether and how canagliflozin, an SGLT2 inhibitor, has been used in patients with T1DM, and whether
Erica A. Voss, Zhong Yuan, Saberi Rana Ali, Rafia Bosan, Efe Eworuke, Jack Brewster, Bogdan Vlacho, Berta Fernández‐Camins, Sergio Fernández‐Bertolín, Sergio Fonseca, Carolyn Jeffcoat, Lu Wang   +11 more
wiley   +1 more source

Prediction Models for Readmission Using Home Healthcare Notes and OMOP-CDM

This study developed readmission prediction models using Home Healthcare (HHC) documents via natural language processing (NLP). An electronic health record of Ajou University Hospital was used to develop prediction models (A reference model using only structured data, and an NLP-enriched model with structured and unstructured data). Among 573 patients,
Gan, Sujin, Kim, Chungsoo, Lee, Dong Yun, Park, Rae Woong   +3 more
openaire   +2 more sources

Converting Entity-Attribute-Value Data Sources to OMOP’s CDM: Lessons Learned

Clinical data repositories often use entity-attribute-value (EAV) data models. To be valuable for secondary use, these health data can be transformed to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The present paper describes the lessons learned from such an endeavour based on the concept of registering transformation ...
Florian, Katsch, Rada, Hussein, Georg, Duftschmid   +2 more
openaire   +2 more sources

How to customize common data models for rare diseases: an OMOP-based implementation and lessons learned

Orphanet Journal of Rare Diseases
Background Given the geographical sparsity of Rare Diseases (RDs), assembling a cohort is often a challenging task. Common data models (CDM) can harmonize disparate sources of data that can be the basis of decision support systems and artificial ...
Najia Ahmadi, Michele Zoch, Oya Guengoeze, Carlo Facchinello, Antonia Mondorf, Katharina Stratmann, Khader Musleh, Hans-Peter Erasmus, Jana Tchertov, Richard Gebler, Jannik Schaaf, Lena S. Frischen, Azadeh Nasirian, Jiabin Dai, Elisa Henke, Douglas Tremblay, Andrew Srisuwananukorn, Martin Bornhäuser, Christoph Röllig, Jan-Niklas Eckardt, Jan Moritz Middeke, Markus Wolfien, Martin Sedlmayr   +22 more
doaj   +1 more source

INSPIRE datahub: a pan-African integrated suite of services for harmonising longitudinal population health data using OHDSI tools

Frontiers in Digital Health
IntroductionPopulation health data integration remains a critical challenge in low- and middle-income countries (LMIC), hindering the generation of actionable insights to inform policy and decision-making.
Tathagata Bhattacharjee, Sylvia Kiwuwa-Muyingo, Chifundo Kanjala, Chifundo Kanjala, Molulaqhooa L. Maoyi, David Amadi, Michael Ochola, Damazo Kadengye, Damazo Kadengye, Arofan Gregory, Agnes Kiragga, Amelia Taylor, Jay Greenfield, Emma Slaymaker, Jim Todd, INSPIRE Network   +15 more
doaj   +1 more source

A Semantic Transformation Methodology for the Secondary Use of Observational Healthcare Data in Postmarketing Safety Studies

Frontiers in Pharmacology, 2018
Background: Utilization of the available observational healthcare datasets is key to complement and strengthen the postmarketing safety studies. Use of common data models (CDM) is the predominant approach in order to enable large scale systematic ...
Anil Pacaci, Anil Pacaci, Suat Gonul, Suat Gonul, A. Anil Sinaci, Mustafa Yuksel, Gokce B. Laleci Erturkmen   +6 more
doaj   +1 more source