Axel Gräwingholt

ORCID: 0000-0003-4778-8731
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About
Contact & Profiles
Research Areas
  • Global Cancer Incidence and Screening
  • Breast Cancer Treatment Studies
  • Colorectal Cancer Screening and Detection
  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Cancer Risks and Factors
  • Clinical practice guidelines implementation
  • Digital Radiography and Breast Imaging
  • Health Systems, Economic Evaluations, Quality of Life
  • Thermoregulation and physiological responses
  • Medical Imaging Techniques and Applications
  • Cancer Genomics and Diagnostics
  • Thermal Regulation in Medicine
  • Advanced X-ray and CT Imaging
  • BRCA gene mutations in cancer
  • Infrared Thermography in Medicine

Paderborn University
2018-2024

Screen
2018-2019

Description: The European Commission Initiative for Breast Cancer Screening and Diagnosis guidelines (European Guidelines) are coordinated by the Commission's Joint Research Centre. target audience includes women, health professionals, policymakers. Methods: An international guideline panel of 28 multidisciplinary members, including patients, developed questions corresponding recommendations that were informed systematic reviews evidence conducted between March 2016 December 2018. GRADE...

10.7326/m19-2125 article EN Annals of Internal Medicine 2019-11-25

Neither breast cancer prevention and early-detection programs, nor their outcomes, are uniform across Europe. This article describes the rationale, methods, process for development of European Commission (EC) Initiative on Breast Cancer Screening Diagnosis Guidelines. To be consistent with standards set by Institute Medicine others, EC followed 6 general principles. First, selected, via an open call, a panel broad representation areas expertise. Second, it ensured that all recommendations...

10.7326/m18-3445 article EN Annals of Internal Medicine 2019-07-22

Image-derived artificial intelligence (AI)-based risk models for breast cancer have shown high discriminatory performances compared with clinical based on family history and lifestyle factors. However, little is known about their generalizability across European screening settings. We therefore investigated the of an AI-based model in Using four populations three countries (Italy, Spain, Germany) screened between 2009 2020 women aged 45–69, we performed a nested case-control study to assess...

10.1016/j.lanepe.2023.100798 article EN cc-by The Lancet Regional Health - Europe 2023-12-06

Abstract Background During healthcare guideline development, panel members often have implicit, different definitions of health outcomes that can lead to misunderstandings about how important these are and balance benefits harms. McMaster GRADE Centre researchers developed ‘health outcome descriptors’ for standardizing descriptions overcoming problems support the European Commission Initiative on Breast Cancer (ECIBC) Guideline Development Group (GDG). We aimed determine which aspects...

10.1186/s12955-020-01338-8 article EN cc-by Health and Quality of Life Outcomes 2020-06-05

The randomized controlled trial comparing digital breast tomosynthesis and synthetic 2D mammograms (DBT + SM) versus mammography (DM) (the To-Be 1 trial), 2016-2017, did not result in higher cancer detection for DBT SM. We aimed to determine if negative cases prior interval consecutive screen-detected cancers from SM were due interpretive error. Five external radiologists performed the individual blinded review of 239 screening examinations (90 true negative, 39 false positive, 19 cancer, 91...

10.1186/s13244-023-01604-5 article EN cc-by Insights into Imaging 2024-02-08

Background and objectivesBreast cancer is one of the greatest global health concerns for women, with rising incidence rates mortality projections, while affordability access to mammography screening diagnosis, especially in low- middle-income countries, remain a challenge. This retrospective clinical validation study evaluated breast pre-screening solution (BCPS) based on commercially available smartphone thermal imaging sensor powered by artificial intelligence. The purpose was measure...

10.14218/csp.2023.00034s article EN cc-by-nc Cancer Screening and Prevention 2024-03-25

Abstract Background: Image-derived AI risk models for breast cancer have shown high discriminatory performances compared with clinical based on family history and lifestyle factors. However, little is known about their generalizability across different screening settings feasibility. Purpose: To investigate the predictive performance of a clinically used image-derived AI-based model in multiple European populations. Methods: Four mammographic populations three countries screened between...

10.1158/1538-7445.sabcs23-ps10-08 article EN Cancer Research 2024-05-02

Zusammenfassung Hintergrund Dank Mammographie-Screening-Programmen (MSP) kann Brustkrebs erwiesenermaßen in früheren Stadien entdeckt werden, was weniger eingreifende Therapien erlaubt und zu einem besseren Überleben führt. Kritisch beurteilt werden die beträchtliche Zahl der Intervallkarzinome (IBC) zusätzlich notwendige Abklärungen, bei denen sich Mehrzahl erweist, dass kein Karzinom vorliegt. Fragestellung In den letzten Jahren wurden von Firmen Universitäten mittels maschinellem Lernen...

10.1007/s00117-024-01345-6 article DE cc-by Deleted Journal 2024-07-17

Analyse der Programm-Sensitivität getrennt nach mammografischem Dichtegrad in einem bevölkerungsbezogenen, digitalen Mammografie-Screening-Programm.

10.1055/s-0038-1641387 article DE RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren 2018-04-01

Analyse von Risikokombinationen für die Inzidenz eines Mammakarzinoms unter Teilnehmerinnen am Mammografie-Screening-Programm Berücksichtigung der bekannten singulären Risikofaktoren Lebensalter und Brustdichte.

10.1055/s-0037-1682128 article DE RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren 2019-03-01
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