Ms Zoja Scekic presented the research paper “Thyroid Hormones Parameter-Based Classification of Patient Health Status: An Analysis of Machine Learning Techniques” on a joint event CMBEBIH & MEDICON 2023 which held place in Sarajevo, Bosnia and Herzegovina from September 14th to September 16th. The paper proposes utilization of machine learning (ML) algorithms for disease diagnosis based on patients’ thyroid hormones levels. The authors are Ms Zoja Scekic, dr Luka Filipovic, prof. Ivana Katnic, prof. Nela Milosevic, and Mr Stevan Sandi.
ABSTRACT – Thyroid autoimmune diseases are widely spread and present in the world population. The problem with these diseases is that giving the diagnosis is often challenging, as the symptoms are similar with some other health problems (for example, depression). This paper proposes utilization of machine learning (ML) algorithms for disease diagnosis based on patients’ thyroid hormones levels. The experiment was done on a dataset that consisting of 2000 data samples with following parameters: TSH, FT4, TT3, SHBG, and T total hormones. Dataset was prepared before feeding into machine learning models. ML algorithms used in the experiment were Logistic Regression, Random Forest Classifier, Naive Bayes, and Support Vector Machines (SVM). For evaluation, multiple metrics were used: confusion matrix, precision, recall, and accuracy. The whole process could be more efficient and accurate with use of good quality artificial intelligence systems as help in making a better diagnosis.