From Syntactic to Semantic Interoperability Using a Hyperontology in the Oncology Domain.

Interoperability is crucial to overcoming various challenges of data integration in the healthcare domain. While OMOP and FHIR data standards handle syntactic heterogeneity among heterogeneous data sources, ontologies support semantic interoperability to overcome the complexity and disparity of healthcare data. This study proposes an ontological approach in the context of the EUCAIM project to support semantic interoperability among distributed big data repositories that have applied heterogeneous cancer image data models using a semantically well-founded Hyperontology for the oncology domain.

External validation of models to estimate gestational age in the second and third trimester using ultrasound: A prospective multicentre observational study.

Objectives: Accurate assessment of gestational age (GA) is important at both individual and population levels. The most accurate way to estimate GA in women who book late in pregnancy is unknown. The aim of this study was to externally validate the accuracy of equations for GA estimation in late pregnancy and to identify the best equation for estimating GA in women who do not receive an ultrasound scan until the second or third trimester.

Prenatal diagnosis of pontocerebellar hypoplasia with postnatal follow-up.

Objective: To describe the MR features enabling prenatal diagnosis of pontocerebellar hypoplasia (PCH).

Method: This was a retrospective single monocentre study. The inclusion criteria were decreased cerebellar biometry on dedicated neurosonography and available fetal Magnetic Resonance Imaging (MRI) with PCH diagnosis later confirmed either genetically or clinically on post-natal MRI or by autopsy.

Prior-Guided Attribution of Deep Neural Networks for Obstetrics and Gynecology.

Obstetrics and gynecology (OB/GYN) are areas of medicine that specialize in the care of women during pregnancy and childbirth and in the diagnosis of diseases of the female reproductive system. Ultrasound scanning has become ubiquitous in these branches of medicine, as breast or fetal ultrasound images can lead the sonographer and guide him through his diagnosis. However, ultrasound scan images require a lot of resources to annotate and are often unavailable for training purposes because of confidentiality reasons, which explains why deep learning methods are still not as commonly used to solve OB/GYN tasks as in other computer vision tasks.

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English.

[A pragmatic comparison of fetal biometry curves].

Introduction: The fetal biometrics charts recommended in France for ultrasound screening include measurements of head circumference (HC), biparietal diameter (BIP), abdominal circumference (AC) and femur length (FL). New international growth standards have been recommended since 2022. The aim of this work is to quantitatively describe the differences between these biometric curves.

A Machine Learning Approach for the Prediction of Testicular Sperm Extraction in Nonobstructive Azoospermia: Algorithm Development and Validation Study.

Background: Testicular sperm extraction (TESE) is an essential therapeutic tool for the management of male infertility. However, it is an invasive procedure with a success rate up to 50%. To date, no model based on clinical and laboratory parameters is sufficiently powerful to accurately predict the success of sperm retrieval in TESE.

Imaging Factors Affecting Prenatal Counseling in Orofacial Clefts.

Introduction: We aim to correlate pre- and postnatal data regarding the cleft type and surgical prognostic factors associated to orofacial clefts.

Methods: Retrospective study concerning all cases of orofacial cleft evaluated prenatally (US+/-MRI) between 2015 and 2020 with available postnatal outcomes. We compared prenatal imaging (cleft type and surgical prognostic factors) with postnatal findings.

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.

Predictive factors for survival in patients with oligohydramnios secondary to antenatal kidney disease.

Background: Renal oligohydramnios (ROH) is caused by bilateral congenital abnormalities, either of renal parenchymal or obstructive origin. ROH is a poor prognostic factor of neonatal survival; lung hypoplasia is reported to be the main cause of mortality. We aimed to describe the fetal morbidity and pre- and postnatal mortality in case of ROH due to renal congenital pathologies and to find predictive risk factors for morbidity and mortality.

Prenatal phenotyping: A community effort to enhance the Human Phenotype Ontology.

Technological advances in both genome sequencing and prenatal imaging are increasing our ability to accurately recognize and diagnose Mendelian conditions prenatally. Phenotype-driven early genetic diagnosis of fetal genetic disease can help to strategize treatment options and clinical preventive measures during the perinatal period, to plan in utero therapies, and to inform parental decision-making. Fetal phenotypes of genetic diseases are often unique and at present are not well understood; more comprehensive knowledge about prenatal phenotypes and computational resources have an enormous potential to improve diagnostics and translational research.

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.

Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review.

Background: The applications of artificial intelligence (AI) processes have grown significantly in all medical disciplines during the last decades. Two main types of AI have been applied in medicine: symbolic AI (eg, knowledge base and ontologies) and nonsymbolic AI (eg, machine learning and artificial neural networks). Consequently, AI has also been applied across most obstetrics and gynecology (OB/GYN) domains, including general obstetrics, gynecology surgery, fetal ultrasound, and assisted reproductive medicine, among others.

The Myelic Limited Dorsal Malformation: Prenatal Ultrasonographic Characteristics of an Intermediate Form of Dysraphism.

Objectives: The aim of the study was to report a subtype of dysraphism designated as myelic limited dorsal malformation (MyeLDM) and to describe its characteristics at prenatal ultrasound (US).

Methods: It was a retrospective study from 2014 to 2020 based on second-line US evaluation of patients referred to our institution for myelomeningocele (MMC). Magnetic resonance imaging and acetylcholine esterase evaluation in the amniotic fluid were also offered.

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.

Open fetal surgery for myelomeningocele repair in France.

Introduction: Open fetal myelomeningocele (MMC) surgery is currently the standard of care option for prenatal MMC repair. We described the population referred to our center and reviewed outcome after open fetal MMC repair.

Material And Methods: All patients referred to our center for MMC were reviewed from July 2014 to June 2020.

Effect of intravenous immunoglobulins to postpone the gestational age of first intrauterine transfusion in very severe red blood cell alloimmunization: A case-control study.

Background: Early intrauterine transfusion (IUT) is associated with a higher risk of fetal loss. Our objective was to evaluate the efficiciency of intravenous immunoglobulins (IVIG) to postpone the gestational age at first IUT beyond 20 weeks of gestation (WG) compared to the previous pregnancy in case of very severe red blood cell (RBC) alloimmunization.

Study Design And Methods: Very severe RBC alloimmunization was defined by a high titer of antibodies and a previous pregnancy complicated by a first IUT before 24 WG and/or perinatal death directly related to alloimmunization.

The impact of optimal dating on the assessment of fetal growth.

Background: The impact of using the Intergrowth (IG) dating formulae in comparison to the commonly used Robinson dating on the evaluation of biometrics and estimated fetal weight (EFW) has not been evaluated.

Methods: Nationwide cross-sectional study of routine fetal ultrasound biometry in low-risk pregnant women whose gestational age (GA) had been previously assessed by a first trimester CRL measurement. We compared the CRL-based GA according to the Robinson formula and the IG formula.

Prevention of Neural Tube Defects by Folic Acid Supplementation: A National Population-Based Study.

Folic acid supplementation is recommended for neural tube defect prevention during pregnancy. We conducted an observational, retrospective national registry study to determine the rate of dispensing of periconceptional folic acid after prescription in a sample of French women representative of the general population. Our study population ( = 186,061) was a representative sample of the French population, recorded in the Health Data System database on pharmacy dispensing of medication and mandatory reporting of pregnancy.