ARTIFICIAL INTELLIGENCE IN CELL ANALYSIS FOR DISEASE IDENTIFICATION
Tadas Kraujalis, Rūta Degutytė Abstract This paper presents a review of traditional machine learning algorithms and artificial neural networks for identifying cellular morphological features, subcellular structures, changes in cell division, and viability. It also discusses their applications in predicting and diagnosing various diseases. Finally, it addresses the limitations and challenges that still persist in cell…