Key result
AI tool use is linked to higher perceived diagnostic success in cardiovascular disease detection.
Why the study?
The increasing rate of CVDs poses challenges to early detection and personalized treatment, prompting examination of the potential of AI in CVD diagnosis and management.
Does the adoption of Artificial Intelligence in clinical practice improve perceived diagnostic success and treatment personalization for cardiovascular diseases among healthcare professionals in Punjab, Pakistan?
Cross-Sectional (n=300)
Yes
Does the adoption of Artificial Intelligence in clinical practice improve perceived diagnostic success and treatment personalization for cardiovascular diseases among healthcare professionals in Punjab, Pakistan?
Answers are grounded in this paper and cite their sources.
This survey of healthcare professionals in Pakistan demonstrates a strong perceived correlation between AI utilization and improved diagnostic accuracy and personalized treatment planning in cardiovascular care.
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.
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Shabeer et al. (2025) conducted a cross-sectional in Cardiovascular diseases (early diagnosis and management) (n=300). Artificial Intelligence usage in cardiovascular diagnosis vs. No Artificial Intelligence usage in diagnosis was evaluated on Perceived diagnostic success in early detection of cardiovascular diseases (p=<0.001). Artificial intelligence usage in cardiovascular diagnosis was associated with higher perceived diagnostic success among surveyed healthcare professionals.
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