Effectiveness of Damoctocog Alfa Pegol to Treat Patients With Hemophilia A Enrolled in the ATHNdataset.

Objectives: Health information for 17 109 people living with hemophilia A (PLwHA) is contained within the ATHNdataset. We aimed to evaluate the real-world effectiveness of damoctocog alfa pegol (BAY 94-9027, Jivi®) for hemophilia A.

Methods: The ATHNdataset was queried for PLwHA receiving damoctocog alfa pegol between January 1, 2010 and April 30, 2022.

SemOntoMap: A Hybrid Approach for Semantic Annotation of Clinical Texts.

This study addresses the challenge of leveraging free-text descriptions in Electronic Health Records (EHR) for clinical research and healthcare improvement. Despite the potential of this data, its direct interpretation by computers is limited. Semantic annotation emerges as a method to make EHR free text machine-interpretable but struggles with specific domain ontologies and faces heightened difficulties in psychiatry.

Predicting treatment resistance in schizophrenia patients: Machine learning highlights the role of early pathophysiologic features.

Detecting patients with a high-risk profile for treatment-resistant schizophrenia (TRS) can be beneficial for implementing individually adapted therapeutic strategies and better understanding the TRS etiology. The aim of this study was to explore, with machine learning methods, the impact of demographic and clinical patient characteristics on TRS prediction, for already established risk factors and unexplored ones. This was a retrospective study of 500 patients admitted during 2020 to the University Hospital Group for Paris Psychiatry.

Variability in the prevalence of inappropriate medication use among older adults: A review highlighting the importance of screening methods and database types.

Aims: The global older population is growing rapidly, and the rise in polypharmacy has increased potentially inappropriate medication (PIM) encounters. PIMs pose health risks, but detecting them automatically in large medical databases is complex. This review aimed to uncover PIM prevalence in individuals aged 65 years or older using health databases and emphasized the risk of underestimating PIM prevalence due to underutilization of detection tools.

Knowledge Representation and Management 2022: Findings in Ontology Development and Applications.

Objectives: To select, present, and summarize the best papers in 2022 for the Knowledge Representation and Management (KRM) section of the International Medical Informatics Association (IMIA) Yearbook.

Methods: We conducted PubMed queries and followed the IMIA Yearbook guidelines for performing biomedical informatics literature review to select the best papers in KRM published in 2022.

Results: We retrieved 1,847 publications from PubMed.

Interprofessional clinical decision-making process in health: A scoping review.

Aims: To describe the key elements of the interprofessional decision-making process in health, based on published scientific studies. To describe the authors, reviews and subject matter of those publications.

Design: Scoping review of the literature.

An Ontology Design Pattern for Modeling Experimental Paradigms.

We present an ontology design pattern for modeling scientific experiments and examinations conducted in a clinical research study. Integrating heterogeneous data into a common ontological model is a challenge, redoubled if we want them to be explored later. In order to facilitate the development of dedicated ontological modules, this design pattern relies on invariants, is centered on the event of the experiment, and keeps the link to the original data.

Ontology-Based Semantic Annotation of French Psychiatric Clinical Documents.

Building a timeline of psychiatric patient profiles can answer many valuable questions, such as how important medical events affect the progression of psychosis in patients. However, the majority of text information extraction and semantic annotation tools, as well as domain ontologies, are only available in English and cannot be easily extended to other languages, due to fundamental linguistic differences. In this paper, we describe a semantic annotation system based on an ontology developed in the PsyCARE framework.

Ontological Modeling of Clinical Study Forms.

The use of eCRFs is now commonplace in clinical research studies. We propose here an ontological model of these forms allowing to describe them, to express their granularity and to link them to the relevant entities of the study in which they are used. It has been developed in a psychiatry project but its generality may allow a wider application.

Knowledge Representation and Management: Notable Contributions in 2021.

Objectives: To select, present, and summarize the best papers in the field of Knowledge Representation and Management (KRM) published in 2021.

Methods: Following the International Medical Informatics Association (IMIA) Yearbook guidelines, a comprehensive and standardized review of the biomedical informatics literature was performed to select the best KRM papers published in 2021, based on PubMed queries.

Results: A total of 1,231 publications were retrieved from PubMed.

Qualitative Evaluation of a Drug Terminology Server.

Background: Although the drug is finished, identifiable, there is no universally accepted standard for naming them. The objective of this work is to evaluate qualitatively the HeTOP drug terminology server by two categories of students: (a) pharmacy students and (b) a control group.

Methods: A formal evaluation was built to measure the perception of users about the HeTOP drug server, using the three mains questions about "teaching interest", "skill interest" (or competence) and "ergonomics".

Pattern-Based Logical Definitions of Prenatal Disorders Grounded on Dispositions.

Biomedical ontologies define concepts having biomedical significance and the semantic relations among them. Developing high-quality and reusable ontologies in the biomedical domain is a challenging task. Pattern-based ontology design is considered a promising approach to overcome the challenges.

Temporal Medical Knowledge Representation Using Ontologies.

Representing temporal information is a recurrent problem for biomedical ontologies. We propose a foundational ontology that combines the so-called three-dimensional and four-dimensional approaches in order to be able to track changes in an individual and to trace his or her medical history. This requires, on the one hand, associating with any representation of an individual the representation of his or her life course and, on the other hand, distinguishing the properties that characterize this individual from those that characterize his or her life course.

The BMS-LM ontology for biomedical data reporting throughout the lifecycle of a research study: From data model to ontology.

Biomedical research data reuse and sharing is essential for fostering research progress. To this aim, data producers need to master data management and reporting through standard and rich metadata, as encouraged by open data initiatives such as the FAIR (Findable, Accessible, Interoperable, Reusable) guidelines. This helps data re-users to understand and reuse the shared data with confidence.

Knowledge Representation and Management: Interest in New Solutions for Ontology Curation.

Objective: To select, present and summarize some of the best papers in the field of Knowledge Representation and Management (KRM) published in 2020.

Methods: A comprehensive and standardized review of the medical informatics literature was performed to select the most interesting papers of KRM published in 2020, based on PubMed queries. This review was conducted according to the IMIA Yearbook guidelines.

Use of a modular ontology and a semantic annotation tool to describe the care pathway of patients with amyotrophic lateral sclerosis in a coordination network.

The objective of this study was to describe the care pathway of patients with amyotrophic lateral sclerosis (ALS) based on real-life textual data from a regional coordination network, the Ile-de-France ALS network. This coordination network provides care for 92% of patients diagnosed with ALS living in Ile-de-France. We developed a modular ontology (OntoPaRON) for the automatic processing of these unstructured textual data.

Design and Use of Semantic Resources: Findings from the Section on Knowledge Representation and Management of the 2020 International Medical Informatics Association Yearbook.

Objective: To select, present, and summarize the best papers in the field of Knowledge Representation and Management (KRM) published in 2019.

Methods: A comprehensive and standardized review of the biomedical informatics literature was performed to select the most interesting papers of KRM published in 2019, based on PubMed and ISI Web Of Knowledge queries.

Results: Four best papers were selected among 1,189 publications retrieved, following the usual International Medical Informatics Association Yearbook reviewing process.

Manual Evaluation of the Automatic Mapping of International Classification of Diseases (ICD)-11 (in French).

A lexical method was used to map ICD-11 to the terminologies included in the HeTOP server. About half of ICD-11 codes (47.76%) were mapped to at least one concept.

Epigenetic deregulation of GATA3 in neuroblastoma is associated with increased GATA3 protein expression and with poor outcomes.

To discover epigenetic changes that may underly neuroblastoma pathogenesis, we identified differentially methylated genes in neuroblastoma cells compared to neural crest cells, the presumptive precursors cells for neuroblastoma, by using genome-wide DNA methylation analysis. We previously described genes that were hypermethylated in neuroblastoma; in this paper we report on 67 hypomethylated genes, which were filtered to select genes that showed transcriptional over-expression and an association with poor prognosis in neuroblastoma, highlighting GATA3 for detailed studies. Specific methylation assays confirmed the hypomethylation of GATA3 in neuroblastoma, which correlated with high expression at both the RNA and protein level.

Formal Medical Knowledge Representation Supports Deep Learning Algorithms, Bioinformatics Pipelines, Genomics Data Analysis, and Big Data Processes.

Objective: To select, present, and summarize the best papers published in 2018 in the field of Knowledge Representation and Management (KRM).

Methods: A comprehensive and standardized review of the medical informatics literature was performed to select the most interesting papers published in 2018 in KRM, based on PubMed and ISI Web Of Knowledge queries.

Results: Four best papers were selected among the 962 publications retrieved following the Yearbook review process.

Using Equivalent Classes of an Ontology to Understand Care Pathway in Amyotrophic Lateral Sclerosis.

To understand the home-based difficulties encountered in the health care pathways of patients with Amyotrophic Lateral Sclerosis (ALS), we must annotate a large amount of textual data, from a database created by the ALS Île de France coordination network. For this purpose, we have developed a modular ontology, consisting of four modules, and a semantic annotation tool integrating the created ontology. The specificity of our approach is the creation of equivalent classes at different levels of the ontology.

A Novel Intelligent Scan Assistant System for Early Pregnancy Diagnosis by Ultrasound: Clinical Decision Support System Evaluation Study.

Background: Early pregnancy ultrasound scans are usually performed by nonexpert examiners in obstetrics/gynecology (OB/GYN) emergency departments. Establishing the precise diagnosis of pregnancy location is key for appropriate management of early pregnancies, and experts are usually able to locate a pregnancy in the first scan. A decision-support system based on a semantic, expert-validated knowledge base may improve the diagnostic performance of nonexpert examiners for early pregnancy transvaginal ultrasound.

As Ontologies Reach Maturity, Artificial Intelligence Starts Being Fully Efficient: Findings from the Section on Knowledge Representation and Management for the Yearbook 2018.

Objectives:  To select, present, and summarize the best papers published in 2017 in the field of Knowledge Representation and Management (KRM).

Methods:  A comprehensive and standardized review of the medical informatics literature was performed to select the most interesting papers of KRM published in 2017, based on a PubMed query.

Results:  In direct line with the research on data integration presented in the KRM section of the 2017 edition of the International Medical Informatics Association (IMIA) Yearbook, the five best papers for 2018 demonstrate even further the added-value of ontology-based integration approaches for phenotype-genotype association mining.

Semantic interoperability challenges to process large amount of data perspectives in forensic and legal medicine.

This article is a position paper dealing with semantic interoperability challenges. It addresses the Variety and Veracity dimensions when integrating, sharing and reusing large amount of heterogeneous data for data analysis and decision making applications in the healthcare domain. Many issues are raised by the necessity to conform Big Data to interoperability standards.

A Modular Ontology for Modeling Service Provision in a Communication Network for Coordination of Care.

This paper presents a modular ontology of health care in the context in Amyotrophic Lateral Sclerosis. 4 modules cover socio-environmental, medical, and care coordination aspects of the domain. They are organized by a core module.