A suggested way forward for adoption of AI-Enabled digital pathology in low resource organizations in the developing world

Talat Zehra, Anil Parwani, Jamshid Abdul-Ghafar, Zubair Ahmad

Research output: Contribution to journalReview articlepeer-review

1 Citation (Scopus)

Abstract

Low- and middle-income countries (LMICs) represent a big source of data not only for endemic diseases but also for neoplasms. Data is the fuel which drives the modern era. Data when stored in digital form can be used for constructing disease models, analyzing disease trends and predicting disease outcomes in various demographic regions of the world. Most labs in developing countries don’t have resources such as whole slide scanners or digital microscopes. Owing to severe financial constraints and lack of resources, they don’t have the capability to handle large amounts of data. Due to these issues, precious data cannot be saved and utilized properly. However, digital techniques can be adopted even in low resource settings with significant financial constraints. In this review article, we suggest some of the options available to pathologists in developing countries which can enable them to start their digital journey and move forward despite resource-poor health system.

Original languageEnglish
Article number68
JournalDiagnostic Pathology
Volume18
Issue number1
DOIs
Publication statusPublished - Dec 2023

Keywords

  • Artificial intelligence
  • Developing countries
  • Neoplasms
  • Pathologists

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