The paper explores advanced methodologies for diagnosing diseases by comparing normal and pathological cells in various tissues. It highlights the effectiveness of both manual and automated techniques in detecting a wide range of health issues, despite some limitations. The study emphasizes the development of mathematical algorithms for image processing and pattern recognition, which enhance the speed and efficiency of diagnostics while maintaining sensitivity. This approach aims to improve patient health assessments and drug research by facilitating intelligent recognition of cellular anomalies.
