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| http://dx.doi.org/10.1136/jamia.2010.003756 | DOI Listing |
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Development of a text mining algorithm for identifying adverse drug reactions in electronic health records.
JAMIA Open
October 2024
Department of Clinical Pharmacy, University Medical Centre Utrecht, 3584 CX Utrecht, The Netherlands.
Objective: Adverse drug reactions (ADRs) are a significant healthcare concern. They are often documented as free text in electronic health records (EHRs), making them challenging to use in clinical decision support systems (CDSS). The study aimed to develop a text mining algorithm to identify ADRs in free text of Dutch EHRs.
View Article and Find Full Text PDFFeasibility of disease terminology systems for mapping orphan conditions and therapeutic indications of designated orphan medicines in the European Union.
Eur J Pharm Sci
November 2024
Dutch Medicines Evaluation Board, Utrecht, the Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands.
Background: In the European Union, rare diseases are defined as diseases that affect maximum 5 in 10,000 citizens. These diseases are typically associated with a high unmet medical need. To stimulate development and authorisation of medicines for rare diseases ('orphan conditions'), the European Commission (EC) can grant orphan designations.
View Article and Find Full Text PDFPrevalence and clinical characteristics of patients with rheumatoid arthritis with interstitial lung disease using unstructured healthcare data and machine learning.
RMD Open
January 2024
Medical Department, Bristol-Myers Squibb Company, Madrid, Spain
Objectives: Real-world data regarding rheumatoid arthritis (RA) and its association with interstitial lung disease (ILD) is still scarce. This study aimed to estimate the prevalence of RA and ILD in patients with RA (RAILD) in Spain, and to compare clinical characteristics of patients with RA with and without ILD using natural language processing (NLP) on electronic health records (EHR).
Methods: Observational case-control, retrospective and multicentre study based on the secondary use of unstructured clinical data from patients with adult RA and RAILD from nine hospitals between 2014 and 2019.
Extracting cancer concepts from clinical notes using natural language processing: a systematic review.
BMC Bioinformatics
October 2023
Department of Health Information Sciences, Faculty of Management and Medical Information Sciences, Kerman University of Medical Sciences, Kerman, Iran.
Background: Extracting information from free texts using natural language processing (NLP) can save time and reduce the hassle of manually extracting large quantities of data from incredibly complex clinical notes of cancer patients. This study aimed to systematically review studies that used NLP methods to identify cancer concepts from clinical notes automatically.
Methods: PubMed, Scopus, Web of Science, and Embase were searched for English language papers using a combination of the terms concerning "Cancer", "NLP", "Coding", and "Registries" until June 29, 2021.
Prevalence of non-alcoholic fatty liver disease in patients with nephrotic syndrome: A population-based study.
World J Hepatol
February 2023
Digestive Disease and Hepatology, Cleveland Clinic Foundation, Cleveland, OH 44111, United States.
Background: Non-alcoholic fatty liver disease (NAFLD) is a global health concern with a prevalence of about 25% amongst United States adults. Its increased prevalence is attributed to increase in patients with obesity and metabolic syndrome, partly due to similar mechanisms of injury. Nephrotic syndrome (NS) is a clinical entity resulting from extensive proteinuria leading to hypoalbuminemia, hyperlipidemia, edema, and other complications.
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