In this episode of the AI in Healthcare podcast, we explore new research on using gradient-boosted models to predict coronary artery disease. 00:00 Introduction to AI in Healthcare Podcast00:09 Gradient-Boosted Models in Coronary Artery Disease Prediction00:47 Improving Referral Pathways with Transparent Models01:18 Pragmatic Steps for Clinical Implementation01:40 Key Takeaways and Recommendations01:55 Conclusion Williams MC, Guimaraes ARM, Jiang M, Kwieciński J, Weir-McCall JR, Adamson PD, et al. Machine learning to predict high-risk coronary artery disease on CT in the SCOT-HEART trial. Open Heart. 2025 Sep 1;12(2):e003162. doi:10.1136/openhrt-2025-003162. PMCID: PMC12406813. PMID: 40889953.

In this episode of the AI in Healthcare podcast, we explore new research on using gradient-boosted models to predict coronary artery disease. 00:00 Introduction to AI in Healthcare Podcast00:09 Gradient-Boosted Models in Coronary Artery Disease Prediction00:47 Improving Referral Pathways with Transparent Models01:18 Pragmatic Steps for Clinical Implementation01:40 Key Takeaways and Recommendations01:55 ConclusionWilliams MC, Guimaraes ARM, Jiang M, Kwieciński J, Weir-McCall JR, Adamson PD, et al. Machine learning to predict high-risk coronary artery disease on CT in the SCOT-HEART trial. Open Heart. 2025 Sep 1;12(2):e003162. doi:10.1136/openhrt-2025-003162. PMCID: PMC12406813. PMID: 40889953.  

AI in Healthcare

Sharpening Coronary CT Triage: Practical AI Tools for Chest Pain Clinics

In this episode of the AI in Healthcare podcast, we break down a new study by Jeong and colleagues that explores the impact of AI assistance on radiologist reading times and workflow efficiency. One‑line takeaway: AI assistance reduced reading time and improved throughput for bone‑age radiograph interpretation in a real‑world retrospective cohort. ReferenceThe Impact of Artificial Intelligence on Radiologists’ Reading Time in Bone Age Radiograph Assessment Citation: Jeong S, Han K, Kang Y, et al. Journal of Imaging Informatics in Medicine. 2025 Aug;38(4):1915‑1923.https://pubmed.ncbi.nlm.nih.gov/39528879/

In this episode of the AI in Healthcare podcast, we break down a new study by Jeong and colleagues that explores the impact of AI assistance on radiologist reading times and workflow efficiency.One‑line takeaway: AI assistance reduced reading time and improved throughput for bone‑age radiograph interpretation in a real‑world retrospective cohort.ReferenceThe Impact of Artificial Intelligence on Radiologists’ Reading Time in Bone Age Radiograph Assessment Citation: Jeong S, Han K, Kang Y, et al. Journal of Imaging Informatics in Medicine. 2025 Aug;38(4):1915‑1923.https://pubmed.ncbi.nlm.nih.gov/39528879/

AI assisted Pediatric Bone Age Workflow Study

Join us on the AI in Healthcare podcast as we discuss into the groundbreaking development of VentAI, a reinforcement learning algorithm designed to recommend optimal ventilator settings for ICU patients. 00:00 Introduction to AI in Healthcare00:06 VentAI: Revolutionizing Ventilator Settings00:20 Study and Validation of VentAI00:54 Performance and Comparison with Clinician Care01:37 The Role of AI in Clinical Decision Making01:56 Future of AI in Intensive Care02:02 Conclusion and Follow Us

Join us on the AI in Healthcare podcast as we discuss into the groundbreaking development of VentAI, a reinforcement learning algorithm designed to recommend optimal ventilator settings for ICU patients. 00:00 Introduction to AI in Healthcare00:06 VentAI: Revolutionizing Ventilator Settings00:20 Study and Validation of VentAI00:54 Performance and Comparison with Clinician Care01:37 The Role of AI in Clinical Decision Making01:56 Future of AI in Intensive Care02:02 Conclusion and Follow Us

Revolutionizing ICU Care How AI Optimizes Ventilator Settings

Updates into the world of artificial intelligence and explore the most recent trends and developments in healthcare.

Updates into the world of artificial intelligence and explore the most recent trends and developments in healthcare. 

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AI in Healthcare

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