Leveraging digital pathology and AI to transform clinical diagnosis in developing countries

Computational pathology holds the promise of transforming the field of pathology by enabling faster and more accurate diagnosis and treatment planning. Digital pathology and artificial intelligence (AI) play a pivotal role in this transformation, offering more objective and precise diagnoses, increased efficiency, and the ability to handle large volumes of data. However, several translation barriers must be addressed to realize this potential, especially in developing countries. These barriers include the need for standardization of image acquisition and analysis, the limited availability of large, annotated image datasets, and a lack of computational expertise among pathologists. Overcoming these challenges requires collaboration among pathologists, computer scientists, and other experts, as well as the development of new technologies and algorithms. Despite these advancements, standardization and the creation of extensive annotated datasets remain critical issues. Addressing these barriers through collaborative efforts and technological innovation can significantly improve patient outcomes and reduce healthcare costs, making computational pathology a powerful tool in modern medicine in resource-limited settings.