E-submission
Search
- Page Path
- HOME > Search
Original Article
- Attitudes toward artificial intelligence in pathology: a survey-based study of pathologists in northern India
- Manupriya Sharma, Kavita Kumari, Navpreet Navpreet, Sushma Bharti, Rajneesh Kumari
- J Pathol Transl Med. 2025;59(6):382-389. Published online October 2, 2025
- DOI: https://doi.org/10.4132/jptm.2025.07.10
- 2,749 View
- 158 Download
-
Abstract
PDF
Supplementary Material - Background
Artificial intelligence (AI) is transforming pathology by enhancing diagnostic accuracy, efficiency, and workflow standardization. Despite its growing presence, AI adoption remains limited, particularly in resource-constrained settings like India. This study assessed the knowledge, awareness, and perceptions of AI among pathologists in Northern India. Methods: A cross-sectional survey was conducted among 138 practicing pathologists in Northern India between April and June 2024. A structured online questionnaire was used to collect data on demographics, AI awareness, self-reported knowledge, sources of AI education, technological proficiency, and interest in AI-related training programs. Data analysis included descriptive statistics and chi-square tests, with p < .05 considered statistically significant. Results: AI awareness was high (88.4%), with significant sex differences (93.5% in females vs. 78.3% in males, p = .008). However, formal AI training was limited (6.5%), and only 16.7% had used AI as a diagnostic tool. Academic pathologists were more likely to engage with AI literature than their non-academic counterparts (p = .003). Interest in AI workshops was strong (92.8%). Access to whole slide imaging (WSI) correlated with higher AI knowledge (p = .008), as did self-reported technological proficiency (p = .001). Conclusions: Despite high AI awareness among pathologists, significant gaps remain in training, infrastructure, and practical application. Expanding access to digital pathology tools like WSI and improving digital literacy could facilitate AI adoption. Structured educational programs and greater investment in digital infrastructure are crucial for integrating AI into pathology practice.
First
Prev
