Data Analysis on Dental Patients with Medical Co-Morbidities Using Machine Learning Algorithm

From the eve of the advancement of medical science, oral and dental health care has gained importance with severe medical health issues and medical disabilities. The dentist must be careful about any medically compromised patient providing dental or oral treatment as that should be safe and effective. In this paper, we have explained dental patients with medical co-morbidities for a real dataset to study the pervasiveness of medical co-morbidities in patients who need dental treatments. We have collected around 3600 instances with multiple comorbidities of patients visited for dental treatment and regular check-ups from January 2020 to February 2022 in three different hospitals in Bangladesh. From 3600 patients, more than $30 \%$ patients aged above 30 years had co-morbidities in this study. The absolute view of this study is to preprocess the data and then show correlations among them. Our target is to improve the performance using machine learning classifiers and create a training data set. We have used artificial neural network (ANN) and random forest (RF) classifiers and got accuracies $\mathbf{9 8 . 6 3 \%}$ for ANN and $\mathbf{9 7 . 4 5 \%}$ for RF. Co-morbidity is a co-existing medical condition distinct from a focal state, making the patient look for medical services. Unpleasant health condition is related to complex clinical management and that may increase healthcare costs. This paper also described the relationship between dental patients with medical co-morbidities like hypertension (HTN), Diabetes, Asthma, hypothyroidism, cardiac complications, renal diseases, liver disease, and some oro-pharyngeal complications related to dental diseases, etc.