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[AI based Evaluation of Psychotrauma related to Lahars in the Commune of PrĂȘcheur in the French Antilles].

Sante mentale au Quebec
Objectives Natural disasters have a significant impact on mental health. Data collected from the population offer a unique opportunity for post-disaster monitoring to help identify psychological support needs. The aim of this study is: 1) to identify...

Combining deep neural networks, a rule-based expert system and targeted manual coding for ICD-10 coding causes of death of French death certificates from 2018 to 2019.

International journal of medical informatics
OBJECTIVE: For ICD-10 coding causes of death in France in 2018 and 2019, predictions by deep neural networks (DNNs) are employed in addition to fully automatic batch coding by a rule-based expert system and to interactive coding by the coding team fo...

Validation of a natural language processing algorithm using national reporting data to improve identification of anesthesia-related ADVerse evENTs: The "ADVENTURE" study.

Anaesthesia, critical care & pain medicine
BACKGROUND: Reporting and analysis of adverse events (AE) is associated with improved health system learning, quality outcomes, and patient safety. Manual text analysis is time-consuming, costly, and prone to human errors. We aimed to demonstrate the...

RSV Severe Infection Risk Stratification in a French 5-Year Birth Cohort Using Machine-learning.

The Pediatric infectious disease journal
BACKGROUND: Respiratory syncytial virus (RSV) poses a substantial threat to infants, often leading to challenges in hospital capacity. With recent pharmaceutical developments to be used during the prenatal and perinatal periods aimed at decreasing th...

Evaluation of a machine-learning model based on laboratory parameters for the prediction of acute leukaemia subtypes: a multicentre model development and validation study in France.

The Lancet. Digital health
BACKGROUND: Acute leukaemias are life-threatening haematological cancers characterised by the infiltration of transformed immature haematopoietic cells in the blood and bone marrow. Prompt and accurate diagnosis of the three main acute leukaemia subt...

Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop and validate a natural language processing (NLP) pipeline that detects 18 conditions in French clinical notes, including 16 comorbidities of the Charlson index, while exploring a collaborative and privacy-enhancing workflow.

Performance of a NLP Tool for Text Classification from Orthopaedic Operative Reports, Using Data from the Large Network of Clinical Data Warehouses of the West of France: The HACRO-HUGORTHO Project.

Studies in health technology and informatics
Electronic health data concerning implantable medical devices (IMD) opens opportunities for dynamic real-world monitoring to assess associated risks related to implanted materials. Due to population ageing and expanding demands, total hip, knee, and ...

Beyond Tokens: Fair Evaluation of French Large Language Models for Clinical Named Entity Recognition.

Studies in health technology and informatics
Named Entity Recognition (NER) models based on Transformers have gained prominence for their impressive performance in various languages and domains. This work delves into the often-overlooked aspect of entity-level metrics and exposes significant di...

Secure Extraction of Personal Information from EHR by Federated Machine Learning.

Studies in health technology and informatics
Secure extraction of Personally Identifiable Information (PII) from Electronic Health Records (EHRs) presents significant privacy and security challenges. This study explores the application of Federated Learning (FL) to overcome these challenges wit...

Comparing NER Approaches on French Clinical Text, with Easy-to-Reuse Pipelines.

Studies in health technology and informatics
The task of Named Entity Recognition (NER) is central for leveraging the content of clinical texts in observational studies. Indeed, texts contain a large part of the information available in Electronic Health Records (EHRs). However, clinical texts ...