ARTIFICIAL INTELLIGENCE IN CELL ANALYSIS FOR DISEASE IDENTIFICATION

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 imaging analysis and the restrictions on the broader use of artificial intelligence in medicine.