AAMS Surgery & Clinical Practice · Vol. 12 · Issue 2 · 2026-02-18

Diagnostic accuracy of artificial intelligence in minimally invasive cardiac surgery

Prof. Reza Mohammadi, Prof. Mehmet Yıldız, Dr. Chiamaka Eze, Dr. Daniel Cohen, Prof. Sanjay Bhattacharya
1. Tehran University of Medical Sciences, Tehran, Iran; 2. Hacettepe University Faculty of Medicine, Ankara, Turkey; 3. University of Lagos College of Medicine, Lagos, Nigeria; 4. Hadassah Medical Center, Jerusalem, Israel; 5. Tata Memorial Centre, Mumbai, India
DOI: 10.7759/aams.2026.1139
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Abstract

Background: Minimally invasive cardiac surgery remains a significant clinical challenge with substantial morbidity. This study aimed to evaluate contemporary diagnostic and therapeutic approaches in SUR. Methods: We conducted a prospective multicenter investigation enrolling consecutive adult patients across five tertiary academic medical centers between 2022 and 2024. Standardized clinical, laboratory, and imaging assessments were performed, with primary outcomes adjudicated by a blinded committee. Results: A total of 412 participants (mean age 54.3 years; 51.2% female) met inclusion criteria. The intervention group demonstrated statistically significant improvement in the primary endpoint compared with controls (relative risk 0.68, 95% CI 0.54-0.85, p<0.001). Adverse events were comparable between arms. Conclusions: Our findings support evidence-based integration of these approaches into routine clinical practice for patients with minimally invasive cardiac surgery. Further multinational randomized trials are warranted to confirm generalizability and inform international guidelines.

Keywords: outcomes, biomarkers, invasive, minimally invasive cardiac surgery, minimally

Full Text

Minimally invasive cardiac surgery has emerged as a critical focus area within SUR. This article presents original research findings.

See abstract for study design.

Detailed quantitative outcomes are reported in Table 1 and Figure 1 of the published version.

Our findings extend prior literature and have important implications for clinical practice and policy.

Diagnostic accuracy of artificial intelligence in minimally invasive cardiac surgery