ArticleJTCVS open2026
Gender-based differences in perceptions of artificial intelligence in clinical cardiothoracic surgery.
Article in JTCVS open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Artificial Intelligence and the Ethical Foundations of Cardiothoracic Surgery: Evidence, Accountability, and the Limits of Delegated Judgment.Medical sciences (Basel, Switzerland) · 2026Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) is poised to reshape cardiothoracic (CT) surgery. Prior studies suggest different attitudes and adoption rates of AI based on gender. This study explores these gender-based differences further to identify domains in which differences might exist. Methods: A survey addressing the use of AI in CT surgery was created and distributed to members of multiple international CT surgery societies. Results were collected electronically. Responses were scored on a 5-point Likert scale and then collapsed into 3 categories for χ Results: Data from 412 CT surgeons were analyzed, including 344 men and 68 women specializing in cardiac (n = 213) and thoracic (n = 176) surgery. Geographic representation included North America (65%), Europe (24%), and Asia (11%). In comparing subspecialties, female CT surgeons were more likely than male surgeons to assign a limited role to AI. North American female surgeons saw the smallest role for AI. Female surgeons' hopes for AI focused on reductions in administrative burden and efficiency gains, while men sought improved diagnostic accuracy and decision making support. Women were worried about systemic biases and clinical dehumanization, while men were concerned with the technical implementation of AI. Conclusions: Gender is associated with CT surgeons' perceptions of AI in clinical care, with women, particularly thoracic subspecialists, expressing more reservations than men. It is important to understand these different views, as adoption of AI in CT surgery may have an important impact on gender equity in the field.
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