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Jean‐François Chenot

Biographic Data

ID6577200
NAMEJean‐François Chenot
GIVEN NAMESJean‐François
FAMILY NAMEChenot
SIGNATURECHENOT J F
AFFILIATIONSUniversitätsmedizin Greifswald
ORCID0000-0001-8877-2950
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2019
LATEST PUBLICATION YEAR2021
H-INDEX0
  • Predicting Physician Consultations for Low Back Pain Using Claims Data and Population-Based Cohort Data—An Interpretable Machine Learning Approach

    Open Access•Adrian Richter, Julia Truthmann et al.•ARTICLE•International Journal of…•2021

    (1) Background: Predicting chronic low back pain (LBP) is of clinical and economic interest as LBP leads to disabilities and health service utilization. This study aims to build a competitive and interpretable prediction model; (2) Methods: We used clinical and claims data of 3837 participants of a population-based cohort study to predict future LBP consultations (ICD-10: M40.XX-M54.XX). Best subset selection (BSS) was applied in repeated random …

  • Recall accuracy of notifications about incidental findings from an MRI examination

    Katharina Piontek, Adrian Richter et al.•ARTICLE•Journal of Epidemiology and…•2020•References: 26

    Background Self-reports of medical findings are indispensable in clinical practice and research but subject to recall bias. We analysed the recall accuracy of notifications about incidental findings (IFs) from a whole-body MRI examination and assessed determinants of recall error. Methods Data from 3746 participants of a postal follow-up survey conducted on average 2.47 years after examination in the population-based Study of Health in Pomerania …

  • Nephrologists’ perspectives on ambulatory care of patients with non‐dialysis chronic kidney disease ‐ A qualitative study

    Open Access•Annekathrin Haase, Sylvia Stracke et al.•ARTICLE•Health & Social Care in the…•2019•References: 1

    Little is known on the perspectives of nephrologists on managing non-dialysis patients with chronic kidney disease (CKD). The purpose of this qualitative study was to explore the experiences and perspectives of nephrologists regarding the interface with general practitioners (GP) and GPs' management of patients with non-dialysis CKD, so that barriers to cooperation and need for improved management can be identified. Twenty semi-structured intervi…

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  • Nephrologists’ perspectives on ambulatory care of patients with non‐dialysis chronic kidney disease ‐ A qualitative study

    Open Access•Annekathrin Haase, Sylvia Stracke et al.•ARTICLE•Health & Social Care in the…•2019•References: 1

    Little is known on the perspectives of nephrologists on managing non-dialysis patients with chronic kidney disease (CKD). The purpose of this qualitative study was to explore the experiences and perspectives of nephrologists regarding the interface with general practitioners (GP) and GPs' management of patients with non-dialysis CKD, so that barriers to cooperation and need for improved management can be identified. Twenty semi-structured intervi…

  • Recall accuracy of notifications about incidental findings from an MRI examination

    Katharina Piontek, Adrian Richter et al.•ARTICLE•Journal of Epidemiology and…•2020•References: 26

    Background Self-reports of medical findings are indispensable in clinical practice and research but subject to recall bias. We analysed the recall accuracy of notifications about incidental findings (IFs) from a whole-body MRI examination and assessed determinants of recall error. Methods Data from 3746 participants of a postal follow-up survey conducted on average 2.47 years after examination in the population-based Study of Health in Pomerania …

  • Predicting Physician Consultations for Low Back Pain Using Claims Data and Population-Based Cohort Data—An Interpretable Machine Learning Approach

    Open Access•Adrian Richter, Julia Truthmann et al.•ARTICLE•International Journal of…•2021

    (1) Background: Predicting chronic low back pain (LBP) is of clinical and economic interest as LBP leads to disabilities and health service utilization. This study aims to build a competitive and interpretable prediction model; (2) Methods: We used clinical and claims data of 3837 participants of a population-based cohort study to predict future LBP consultations (ICD-10: M40.XX-M54.XX). Best subset selection (BSS) was applied in repeated random …

Medicine (3 works) · Environmental health (2 works) · Internal Medicine (2 works) · Population (2 works) · Alternative medicine (1 work) · Ambulatory (1 work) · Ambulatory care (1 work) · Artificial Intelligence (1 work) · Chronic Kidney Disease and Diabetes (1 work) · Cognitive psychology (1 work)

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