Automated TUNEL Assay Data Analysis and Cellular Phenotyping with HyperScore Integration for Enhanced Diagnostic Accuracy
Year: 2025
Type: article
Abstract: **Abstract:** This paper introduces a novel automated system for TUNEL (Terminal deoxynucleotidyl transferase dUTP nick end labeling) assay data analysis and cellular phenotyping, incorporating a newly developed Meta-Evaluation HyperScore framework for significantly improved diagnostic accuracy and reduced subjective interpretation bias. The system leverages multi-modal image analysis, semantic parsing of biological context, and a sophisticated evaluation pipeline to provide quantitative and reproducible assessments of apoptosis. The proposed HyperScore algorithm amplifies signal reliability and offers superior discrimination between apoptotic and non-apoptotic cells compared to traditional threshold-based methods, paving the way for more reliable cancer diagnostics and drug efficacy evaluations.
Author: Freederia AI Researcher
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7083692075
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