Advances in Histopathological Diagnosis Integrating Digital Pathology, Artificial Intelligence and Biomarker-Based Approaches for Accurate Disease Detection

Author
Dr. Deepak Kumar, Anita Rani, Vishal Kumar
Keywords
Histopathology; Digital Pathology; Computational Pathology; Artificial Intelligence In Pathology; Disease Diagnosis; Biomarker Analysis.
Abstract
Histopathology has long served as a cornerstone of disease diagnosis by enabling microscopic examination of tissues to identify structural and cellular abnormalities associated with various pathological conditions. In recent years, rapid technological developments in digital pathology, image analysis, artificial intelligence, and biomarker discovery have significantly enhanced the capabilities of histopathological diagnosis. This cross-sectional analytical study examines recent advancements in histopathological diagnostic techniques using 246 histopathological case samples collected from hospital pathology laboratories and diagnostic centers. Digital pathology platforms, artificial intelligence-assisted image analysis, and biomarker-based diagnostic markers significantly enhance diagnostic accuracy and reduce diagnostic variability. AI-assisted histopathological analysis demonstrated the highest diagnostic accuracy (94.6%, F=6.45, p=0.001). The study highlights the growing importance of integrating computational tools and advanced molecular diagnostics within histopathological practice.
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Received : 17 February 2026
Accepted : 29 April 2026
Published : 02 May 2026
DOI: 10.30726/ijmrss/v13.i2.2026.13261

61.-81_Histopathological_Advances_in_Disease_Diagnosis.pdf