Pierre-Yves Louis

Professeur des universités (enseignant-chercheur)

Université de Franche-Comté

France

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Prof. Pierre-Yves Louis is a professor and researcher at Université Bourgogne Franche-Comté in France. His research interests encompass statistical modeling, particularly in connection with stochastic processes, clinical pain assessment, and the effects of physiological factors on athletic performance. He has contributed to various scholarly articles, including studies on urn models and pain evaluation methodologies in clinical settings.

Articles (12)

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2025

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2024

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2021

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2021

Year:

2021

Collaborators (1)

Nicolas coulmy

head of department

FRANCE

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Pierre-Yves Louis

Research Interests

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Articles (12)

Erratum to: “Statistical test for an urn model with random multidrawing and random addition” [Stochastic Process. Appl. 158 (2023) 342-360]

Exploring the effect of the menstrual cycle or oral contraception on elite athletes’ training responses when workload is not objectively quantifiable: the MILS approach and findings from female Olympians

Statistical test for an urn model with random multidrawing and random addition

Un indice de réponse clinique multidimensionnel pour améliorer l’évaluation de la douleur chez les patients souffrant d’un syndrome de douleur rachidienne persistante après une chirurgie rachidienne, une étude multicentrique prospective en vie réelle

Potential estimation model in French alpine skiing - Individual evolution curve and progression typology

Interacting nonlinear reinforced stochastic processes: Synchronization or non-synchronization

Relative age effect in French alpine skiing: Problem and solution

An urn model with random multiple drawing and random addition

An urn model with random multiple drawing and random addition

A Novel Multi-Dimensional Clinical Response Index Dedicated to Improving Global Assessment of Pain in Patients with Persistent Spinal Pain Syndrome after Spinal Surgery, Based on a Real-Life Prospective Multicentric Study (PREDIBACK) and Machine Learning Techniques

Machine Learning Algorithms Provide Greater Prediction of Response to SCS Than Lead Screening Trial: A Predictive AI-Based Multicenter Study

Machine Learning Algorithms Provide Greater Prediction of Response to Scs than Lead Screening Trial: A Predictive AI-Based Multicenter Study

Collaborators (1)

Nicolas coulmy

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