Diagnostic Accuracy of Cytopathological Techniques Evaluating Fine-Needle Aspiration, Molecular Cytology and Artificial Intelligence–Assisted Diagnostics

Dr. Rakesh Singh, Sangeeta Sharma, Ajay Kumar

Cytopathology; Fine-Needle Aspiration Cytology; Diagnostic Accuracy; Molecular Cytology; Immunocytochemistry; Artificial Intelligence in Pathology.

Cytopathology has emerged as an essential diagnostic discipline in modern medicine, offering minimally invasive techniques for the detection and characterization of various diseases, particularly malignancies. This cross-sectional analytical study evaluates the diagnostic accuracy and clinical applicability of cytopathological techniques in disease detection and classification using 232 cytological samples. Fine-needle aspiration cytology combined with immunocytochemical and molecular techniques demonstrates high diagnostic accuracy in detecting malignancies and inflammatory diseases, with AI-assisted cytological image analysis achieving the highest overall accuracy (95.4%, F=7.21, p=0.001). The study highlights the importance of integrating advanced molecular techniques, digital cytology platforms, and AI-based diagnostic tools into cytopathological practice

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