Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Creation and pilot testing of cases for case-based learning: A pedagogical approach for pathology cancer diagnosis

Domaine:

healthcareeducation
Créateur:
ShaSusMicDan
Éditeur:
AOS
Hôte:
Background: Case-based learning (CBL) is an established pedagogical active learning method used in various disciplines and defined based on the field of study and type of case. The utility of CBL for teaching specific aspects of cancer diagnosis to practising pathologists has not been previously studied in sub-Saharan Africa.Objectives: We aimed to pilot test standardised cancer cases on a group of practising pathologists in sub-Saharan Africa to evaluate case content, clarity of questions and delivery of content.Methods: Expert faculty created cases for the four most commonly diagnosed cancers. The format included mini-cases and bullet cases which were all open-ended. The questions dealt with interpretation of clinical information, gross specimen examination, morphologic characteristics of tumours, ancillary testing, reporting and appropriate communication to clinicians.Results: Cases on breast, cervical, prostate and colorectal cancers were tested on seven practising pathologists. Each case took an average of 45–90 min to complete.Questions that were particularly challenging to testers were on:•  Specimens they should have been but for some reason were not exposed to in routine practice.•  Ancillary testing and appropriate tumour staging.New knowledge gained included tumour grading and assessment of radial margins. Revisions to cases were made based on testers’ feedback, which included rewording of questions to reduce ambiguity and adding of tables to clarify concepts.Conclusion: Cases were created for CBL in Kenya, but these are applicable elsewhere in Africa and beyond to teach cancer diagnosis. The pilot testing of cases prepared faculty for the actual CBL course and feedback provided by the testers assisted in improving the questions and impact on day-to-day practice.

Visit

doi.org

Licenses

https://creativecommons.org/licenses/by/4.0

Similaires

Pathology Training for Cancer Diagnosis in AfricaDigital pathology with deep learning for diagnosis of breast cancer in low-resource settingsDigital Pathology and Artificial Intelligence in Resource-limited Laboratories: A New Frontier for Cancer DiagnosisDeep learning for AI-based diagnosis of skin-related neglected tropical diseases: a pilot studyAI-Based Predictive Analysis of Osteoporosis: A Machine Learning Approach for Early DiagnosisAbstract 40: Pathology Training for Cancer Diagnosis in Africa: Perspectives from Two Virtual Courses

Pathology Training for Cancer Diagnosis in Africa

Abstract Objectives In response to requests

Digital pathology with deep learning for diagnosis of breast cancer in low-resource settings

Pathologic assessment of tissue sections is an important part of breast cancer diagnosis, with early

Digital Pathology and Artificial Intelligence in Resource-limited Laboratories: A New Frontier for Cancer Diagnosis

International audience Cancer remains a major global health challenge, with a disprop

Deep learning for AI-based diagnosis of skin-related neglected tropical diseases: a pilot study

ABSTRACT Background Deep learning, which i

AI-Based Predictive Analysis of Osteoporosis: A Machine Learning Approach for Early Diagnosis

In underserved regions like Sub-Saharan Africa, Osteoporosis, a debilitating disease remains one of

Abstract 40: Pathology Training for Cancer Diagnosis in Africa: Perspectives from Two Virtual Courses

Abstract Purpose: The burden of cancer continues to grow in Africa, yet there are t