The AI model achieved an 86% accuracy rate in detecting ovarian cancer, surpassing human experts at 82% and those with less expertise at 77%. Elisabeth Epstein, a professor at Karolinska Institutet, expressed surprise at the AI’s superior performance compared to 33 expert examiners. She emphasized the potential for AI-driven diagnostic support to enhance triage efficiency, reduce errors, and address the shortage of expert examiners in improving ovarian cancer diagnosis.
Epstein highlighted the accessibility of high-quality diagnostics in regions with limited expert access, leading to reduced waiting times, fewer unnecessary interventions, earlier cancer detection, and improved patient outcomes. AI’s role in reducing referrals and misdiagnosis was also noted by researchers.
Dr. Brian Slomovitz from Mount Sinai Medical Center underscored the importance of screening and early detection in reducing ovarian cancer deaths. He suggested incorporating AI-driven support to interpret ultrasound findings, thereby enhancing accuracy and reducing false positives and negatives.
Beyond radiology scans, other factors such as menopausal status, symptoms, and blood test results could be considered in AI modeling to optimize patient care. While AI shows promise in improving cancer diagnostics, Dr. Harvey Castro cautioned about existing limitations and the need for demonstrating a survival benefit for widespread adoption.
Overall, experts are optimistic about AI’s potential to enhance cancer diagnostics and improve patient care.
Health Newsletter: “AI’s Effectiveness Limited by Data Quality and Bias, Study Warns”
In an interview with Fox News Digital, a researcher cautioned that the effectiveness of artificial intelligence (AI) in healthcare may be hindered by bias and the reliance on diverse, high-quality data. The researcher emphasized that AI is not yet fully validated for routine clinical use, and unresolved transparency and regulatory concerns persist.
It was underscored that further research is imperative to assess how well AI can adapt to real-world healthcare settings, its long-term impact on healthcare costs and outcomes, and its ability to accommodate diverse populations and various clinical environments. For more articles on health-related topics, readers are encouraged to visit www.foxnews.com/health.
Despite the promising advancements in AI technology, the researchers involved in the study also acknowledged its potential limitations. Epstein, speaking to Fox News Digital, highlighted that the study was not prospective, necessitating additional data to evaluate its performance in a genuine clinical setting.
Exciting developments are on the horizon as a recent study has revealed that ovarian cancer could potentially be detected early through a new blood test. The research team is preparing to initiate clinical studies at Stockholm South Hospital in Sweden to further investigate this promising discovery.
Epstein emphasized the importance of utilizing AI as a diagnostic tool to support healthcare professionals rather than as a substitute for human physicians. She affirmed that the ultimate responsibility for patient diagnosis and treatment lies with the attending physician.
The collaborative efforts of the Karolinska Institutet research team and the KTH Royal Institute of Technology have paved the way for groundbreaking advancements in healthcare. Funding for the project was generously provided by esteemed organizations such as the Swedish Research Council, the Swedish Cancer Society, the Stockholm Regional Council, the Cancer Research Funds of Radiumhemmet, and the Wallenberg AI, Autonomous Systems, and Software Program (WASP), according to a press release.
Original article source: AI detects ovarian cancer better than human experts in new study.
