Thyroid Diseases Detection Using Evolutionary Machine Learning and Deep Learning : A survey - Kadhem Kreem, Anwar; Majeed Hilal, Osama; Taima Albu-Salih, Alaa (Journal of Al-Qadisiyah for Computer Science and Mathematics, 2025)
This paper presents a survey of studies and research on machine learning techniques, deep learning, as well as research using optimization algorithms, and evolutionary algorithms, in relation to discoveries of diagnosing thyroid disorders. The paper includes an analysis of recent studies. The techniques of researchers in this field of diseases (thyroid diseases) are shown. As well as the results of the aforementioned studies on accuracy factors, Precision, Recall, F1-scor and. Advantages and disadvantages of advanced algorithms. By analyzing the current methods that were surveyed, it was proven that transfer learning techniques, as well as techniques that use optimization algorithms, are the most efficient. In some research, preprocessing plays a major role in obtaining better results in the model training stage.