Xavier Tannier
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View article: A Comprehensive Prospective Cohort in Preventive Medicine: Protocol and Profile of the First 1,000 Participants in a Health Screening Program
A Comprehensive Prospective Cohort in Preventive Medicine: Protocol and Profile of the First 1,000 Participants in a Health Screening Program Open
The Zoī cohort is a prospective longitudinal cohort study, designed to advance evidence-based personalized prevention, by systematically screening for undiagnosed or asymptomatic conditions, identifying early risk markers, and predicting f…
View article: Development of the user-friendly decision aid Rule-based Evaluation and Support Tool (REST) for optimizing the resources of an information extraction task
Development of the user-friendly decision aid Rule-based Evaluation and Support Tool (REST) for optimizing the resources of an information extraction task Open
Rules could be an information extraction (IE) default option, compared to ML and LLMs in terms of sustainability, transferability, interpretability, and development burden. We suggest a sustainable and combined use of rules and ML as an IE…
View article: Multimodal identification of a rare head and neck cancer patient cohort in the clinical data warehouse of Greater Paris Teaching Hospital
Multimodal identification of a rare head and neck cancer patient cohort in the clinical data warehouse of Greater Paris Teaching Hospital Open
View article: Is Multimodal Better? A Systematic Review of Multimodal<i>versus</i>Unimodal Machine Learning in Clinical Decision-Making
Is Multimodal Better? A Systematic Review of Multimodal<i>versus</i>Unimodal Machine Learning in Clinical Decision-Making Open
Machine learning has demonstrated success in clinical decision-making, yet the added value of multimodal approaches over unimodal models remains unclear. This systematic review evaluates studies comparing multimodal and unimodal ML algorit…
View article: Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study
Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study Open
Background Valuable insights gathered by clinicians during their inquiries and documented in textual reports are often unavailable in the structured data recorded in electronic health records (EHRs). Objective This study aimed to highlight…
View article: Clinical trial cohort selection using Large Language Models on n2c2 Challenges
Clinical trial cohort selection using Large Language Models on n2c2 Challenges Open
Clinical trials are a critical process in the medical field for introducing new treatments and innovations. However, cohort selection for clinical trials is a time-consuming process that often requires manual review of patient text records…
View article: Towards Semantic Interoperability Among Heterogeneous Cancer Data Models Using a Layered Modular Hyper-Ontology
Towards Semantic Interoperability Among Heterogeneous Cancer Data Models Using a Layered Modular Hyper-Ontology Open
Semantic interoperability is a growing and challenging subject in the healthcare domain. It aims to ensure a coherent and unambiguous exchange, use, and reuse of health information among different systems and applications. In the context o…
View article: Improving the generalizability of white blood cell classification with few-shot domain adaptation
Improving the generalizability of white blood cell classification with few-shot domain adaptation Open
View article: Prompt Engineering Paradigms for Medical Applications: Scoping Review
Prompt Engineering Paradigms for Medical Applications: Scoping Review Open
Background Prompt engineering, focusing on crafting effective prompts to large language models (LLMs), has garnered attention for its capabilities at harnessing the potential of LLMs. This is even more crucial in the medical domain due to …
View article: Improving Interpretability of Leucocyte Classification with Multimodal Network
Improving Interpretability of Leucocyte Classification with Multimodal Network Open
White blood cell classification plays a key role in the diagnosis of hematologic diseases. Models can perform classification either from images or based on morphological features. Image-based classification generally yields higher performa…
View article: From Syntactic to Semantic Interoperability Using a Hyperontology in the Oncology Domain
From Syntactic to Semantic Interoperability Using a Hyperontology in the Oncology Domain Open
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 inte…
View article: Clinical Research Informatics: Contributions from 2023
Clinical Research Informatics: Contributions from 2023 Open
Summary Objectives: To summarize key contributions to current research in the field of Clinical Research Informatics (CRI) and to select the best papers published in 2023. Methods: A bibliographic search using a combination of MeSH descrip…
View article: Reconnaissance d’entités cliniques en few-shot en trois langues
Reconnaissance d’entités cliniques en few-shot en trois langues Open
View article: LIMICS@DEFT'24 : Un mini-LLM peut-il tricher aux QCM de pharmacie en fouillant dans Wikipédia et NACHOS ?
LIMICS@DEFT'24 : Un mini-LLM peut-il tricher aux QCM de pharmacie en fouillant dans Wikipédia et NACHOS ? Open
National audience
View article: Evaluating Plasmodium falciparum automatic detection and parasitemia estimation: A comparative study on thin blood smear images
Evaluating Plasmodium falciparum automatic detection and parasitemia estimation: A comparative study on thin blood smear images Open
Malaria is a deadly disease that is transmitted through mosquito bites. Microscopists use a microscope to examine thin blood smears at high magnification (1000x) to identify parasites in red blood cells (RBCs). Estimating parasitemia is es…
View article: Predicting the age of field <i>Anopheles</i> mosquitoes using mass spectrometry and deep learning
Predicting the age of field <i>Anopheles</i> mosquitoes using mass spectrometry and deep learning Open
Mosquito-borne diseases like malaria are rising globally, and improved mosquito vector surveillance is needed. Survival of Anopheles mosquitoes is key for epidemiological monitoring of malaria transmission and evaluation of vector control …
View article: Prompt engineering paradigms for medical applications: scoping review and recommendations for better practices
Prompt engineering paradigms for medical applications: scoping review and recommendations for better practices Open
Prompt engineering is crucial for harnessing the potential of large language models (LLMs), especially in the medical domain where specialized terminology and phrasing is used. However, the efficacy of prompt engineering in the medical dom…
View article: Higher-Order unification for free!
Higher-Order unification for free! Open
International audience
View article: Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions
Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions Open
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 wor…
View article: A Benchmark Evaluation of Clinical Named Entity Recognition in French
A Benchmark Evaluation of Clinical Named Entity Recognition in French Open
Background: Transformer-based language models have shown strong performance on many Natural LanguageProcessing (NLP) tasks. Masked Language Models (MLMs) attract sustained interest because they can be adaptedto different languages and sub-…
View article: Development and Validation of a Natural Language Processing Algorithm to Pseudonymize Documents in the Context of a Clinical Data Warehouse
Development and Validation of a Natural Language Processing Algorithm to Pseudonymize Documents in the Context of a Clinical Data Warehouse Open
Objective The objective of this study is to address the critical issue of deidentification of clinical reports to allow access to data for research purposes, while ensuring patient privacy. The study highlights the difficulties faced in sh…
View article: Few-shot clinical entity recognition in English, French and Spanish: masked language models outperform generative model prompting
Few-shot clinical entity recognition in English, French and Spanish: masked language models outperform generative model prompting Open
Large language models (LLMs) have become the preferred solution for many natural language processing tasks. In low-resource environments such as specialized domains, their few-shot capabilities are expected to deliver high performance. Nam…
View article: Natural language processing of multi-hospital electronic health records for public health surveillance of suicidality
Natural language processing of multi-hospital electronic health records for public health surveillance of suicidality Open
View article: Impact of Translation on Biomedical Information Extraction: Experiment on Real-Life Clinical Notes
Impact of Translation on Biomedical Information Extraction: Experiment on Real-Life Clinical Notes Open
Background Biomedical natural language processing tasks are best performed with English models, and translation tools have undergone major improvements. On the other hand, building annotated biomedical data sets remains a challenge. Object…
View article: Prediction of amputation risk of patients with diabetic foot using classification algorithms: A clinical study from a tertiary center
Prediction of amputation risk of patients with diabetic foot using classification algorithms: A clinical study from a tertiary center Open
Diabetic foot ulcers can have vital consequences, such as amputation for patients. The primary purpose of this study is to predict the amputation risk of diabetic foot patients using machine‐learning classification algorithms. In this rese…
View article: Few-shot clinical entity recognition in English, French and Spanish: masked language models outperform generative model prompting
Few-shot clinical entity recognition in English, French and Spanish: masked language models outperform generative model prompting Open
International audience
View article: 460 Enhancing neonatal acidosis prediction: A Machine Learning approach using CTG features and clinical characteristics
460 Enhancing neonatal acidosis prediction: A Machine Learning approach using CTG features and clinical characteristics Open
View article: Re‐evaluating fetal scalp <scp>pH</scp> thresholds: An examination of fetal <scp>pH</scp> variations during labor
Re‐evaluating fetal scalp <span>pH</span> thresholds: An examination of fetal <span>pH</span> variations during labor Open
Introduction Since the 1970s, fetal scalp blood sampling (FSBS) has been used as a second‐line test of the acid–base status of the fetus to evaluate fetal well‐being during labor. The commonly employed thresholds that delineate normal pH (…
View article: Development of a natural language processing model for deriving breast cancer quality indicators : A cross-sectional, multicenter study
Development of a natural language processing model for deriving breast cancer quality indicators : A cross-sectional, multicenter study Open
View article: Impact of the <scp>COVID</scp>‐19 pandemic on clinical presentation, treatments, and outcomes of new breast cancer patients: A retrospective multicenter cohort study
Impact of the <span>COVID</span>‐19 pandemic on clinical presentation, treatments, and outcomes of new breast cancer patients: A retrospective multicenter cohort study Open
Background The SARS CoV‐2 pandemic disrupted healthcare systems. We compared the cancer stage for new breast cancers (BCs) before and during the pandemic. Methods We performed a retrospective multicenter cohort study on the data warehouse …