AIMC Topic: France
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Inferring the locomotor ecology of two of the oldest fossil squirrels: influence of operationalization, trait, body size and machine learning method.
Proceedings. Biological sciences
Nov 13, 2024
Correlations between morphology and lifestyle of extant taxa are useful for predicting lifestyles of extinct relatives. Here, we infer the locomotor behaviour of from the middle Oligocene and from the lower Miocene of France using their femoral mor...
Analysis of nailfold capillaroscopy images with artificial intelligence: Data from literature and performance of machine learning and deep learning from images acquired in the SCLEROCAP study.
Microvascular research
Oct 9, 2024
OBJECTIVE: To evaluate the performance of machine learning and then deep learning to detect a systemic scleroderma (SSc) landscape from the same set of nailfold capillaroscopy (NC) images from the French prospective multicenter observational study SC...
Proof of concept study on early forecasting of antimicrobial resistance in hospitalized patients using machine learning and simple bacterial ecology data.
Scientific reports
Sep 30, 2024
Antibiotic resistance in bacterial pathogens is a major threat to global health, exacerbated by the misuse of antibiotics. In hospital practice, results of bacterial cultures and antibiograms can take several days. Meanwhile, prescribing an empirical...
AI-Safe-C score: Assessing liver-related event risks in patients without cirrhosis after successful direct-acting antiviral treatment.
Journal of hepatology
Sep 20, 2024
BACKGROUND & AIMS: Direct-acting antivirals (DAAs) have considerably improved chronic hepatitis C (HCV) treatment; however, follow-up after sustained virological response (SVR) typically neglects the risk of liver-related events (LREs). This study in...
Incidental pulmonary nodules: Natural language processing analysis of radiology reports.
Respiratory medicine and research
Aug 22, 2024
BACKGROUND: Pulmonary nodules are a common incidental finding on chest Computed Tomography scans (CT), most of the time outside of lung cancer screening (LCS). We aimed to evaluate the number of incidental pulmonary nodules (IPN) found in 1 year in o...
RSV Severe Infection Risk Stratification in a French 5-Year Birth Cohort Using Machine-learning.
The Pediatric infectious disease journal
May 7, 2024
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...
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
May 6, 2024
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...
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
Apr 26, 2024
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...
Real-world artificial intelligence-based interpretation of fundus imaging as part of an eyewear prescription renewal protocol.
Journal francais d'ophtalmologie
Mar 8, 2024
OBJECTIVE: A real-world evaluation of the diagnostic accuracy of the Opthai® software for artificial intelligence-based detection of fundus image abnormalities in the context of the French eyewear prescription renewal protocol (RNO).
[The spring of artificial intelligence: AI vs. expert for internal medicine cases].
La Revue de medecine interne
Feb 7, 2024
INTRODUCTION: The "Printemps de la Médecine Interne" are training days for Francophone internists. The clinical cases presented during these days are complex. This study aims to evaluate the diagnostic capabilities of non-specialized artificial intel...
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