Atena Japlaqi

Digital pathology is an emerging field that combines the latest advancements in digital imagingand computer technology to improve medical diagnosis and patient care. With the advent of artificialintelligence (AI), the field of digital pathology has undergone a significant transformation.This review aims to highlight the current state of the art in digital pathology and the role of AI inmedical diagnosis.Background and aims: The traditional method of pathology diagnosis involves examining tissuesamples under a microscope. However, this process can be time-consuming, labor-intensive, andprone to errors. Digital pathology provides a solution to these challenges, allowing pathologiststo examine high-resolution digital images of tissue samples on a computer screen. The aim of thisreview is to explore the current state of digital pathology and how AI is being used to improvemedical diagnosis.Method: This review includes a comprehensive analysis of the literature related to digital pathologyand the role of AI in medical diagnosis. The research methods used in this review includea systematic search of online databases and a critical evaluation of relevant articles and studies.Results: The use of AI in digital pathology has led to significant advancements in medical diagnosis.AI algorithms can analyze large datasets of medical images, allowing for a faster and moreaccurate diagnosis. AI can also help pathologists detect subtle changes in tissue samples that maybe missed by the human eye. In addition, AI can be used to assist in the identification of cancerouscells and the prediction of disease outcomes.Conclusion: Digital pathology and the use of AI have the potential to revolutionize medicaldiagnosis and patient care. The integration of AI in digital pathology has led to significant improvementsin accuracy, speed, and efficiency. Future research should focus on developing moreadvanced AI algorithms and improving the interoperability of digital pathology systems. Overall,the use of AI in digital pathology is a promising area for future development and research.

digital pathology, artificial intelligence, medical diagnosis, pathology, machine learning, healthcare