The Role of Artificial Intelligence in Early Diagnosis and Management of Cardiovascular Diseases
Hassan Shabeera, Hafiz Muhammad Ali Haiderb, Tamana Khatric, Nouman Khand, A. Rafiquee, Fakhar Anjamf
- aArmed Forces Institute of Cardiology, Rawalpindi, Punjab, Pakistan
- bInternal Medicine, Gulab Devi Chest Hospital, Lahore, Punjab, Pakistan
- cDow University of Health Sciences, Karachi, Sindh, Pakistan
- dKabir Medical College, Gandhara University, Peshawar, KP, Pakistan
- eAssistant Professor, Department of CS and IT, University of Poonch, Rawalakot, Pakistan
- fDepartment of Electrical Engineering, University of Science & Technology, Bannu, KP, Pakistan
Papers open inside SciRah from the original publisher or repository; SciRah never hosts them.
Abstract
The increasing rate of cardiovascular diseases (CVDs) has posed a tremendous challenge to their early detection and personalized treatment. This research examines the potential of Artificial Intelligence (AI) for early detection and management of CVDs, in particular whether it can enhance diagnostic accuracy, personalize treatment guidelines, and reduce healthcare costs. A quantitative methodology was adopted and a survey strategy was employed for collecting primary data from 300 healthcare professionals consisting of cardiologists, general physicians, and professionals in AI fields from Punjab hospitals in Pakistan. The questionnaire was constructed to determine their knowledge, experiences, and perceptions regarding the use of AI in cardiovascular services. Data analysis revealed that application of AI had a strong correlation with increased diagnostic success, evident in a statistically significant chi-square test (p < 0.001). Furthermore, multiple regression analysis revealed that AI, together with years of experience and educational history, is an important contributor to personalizing cardiovascular treatment plans. The results indicate that AI has a key role in making more precise diagnoses and improving treatment methods, which can ultimately decrease the cost of healthcare and enhance patient outcomes. Yet, issues around data privacy, transparency, and clinician confidence in AI systems must be resolved in order for AI to be adopted more widely. Future research is suggested by the study into the integration of AI with other health technologies and the ethics of using AI in clinical practice.
TL;DRApplication of AI had a strong correlation with increased diagnostic success, evident in a statistically significant chi-square test and multiple regression analysis revealed that AI, together with years of experience and educational history, is an important contributor to personalizing cardiovascular treatment plans. (Semantic Scholar)