{
  "id": 637590,
  "title": "AI heart disease prediction tools show promise but are not ready for clinical use: review",
  "url": "https://urgent.news/2026/08/12/ai-heart-disease-prediction-tools-show-promise-but-are-not-ready-for",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-12T06:21:47.000Z",
  "source": {
    "name": "The Hindu Health",
    "slug": "the-hindu-health",
    "url": "https://www.thehindu.com/news/national/karnataka/ai-heart-disease-prediction-tools-show-promise-but-are-not-ready-for-clinical-use-review/article71332372.ece"
  },
  "original_language": "en",
  "account": "Artificial intelligence (AI) holds potential for earlier identification of individuals at risk of cardiovascular disease (CVD) in India, allowing for more personalized prevention strategies. However, AI tools are not yet ready for routine clinical decision-making, according to a systematic review by researchers from the Indian Institute of Science, M.S. Ramaiah University of Applied Sciences, and the London School of Hygiene and Tropical Medicine. The review, published in BMC Medical Informatics and Decision Making, analyzed 30 studies on AI-based CVD prediction models published since 2017. Most models were based on datasets from the U.S., U.K., and South Korea and used machine learning algorithms such as Random Forests, Support Vector Machines, and neural networks. While AI models generally performed as well as or slightly better than conventional risk calculators like the Framingham Risk Score, the evidence is still not adequate for widespread clinical use. Rigorous independent validation, calibration, and assessment of clinical usefulness are necessary before AI tools can guide long-term treatment decisions. A major concern is the lack of evidence showing whether the predicted risk accurately reflects what happens in real-world populations. Most studies assessed discrimination, but none examined calibration or decision-curve analyses. India's unique risk factors and disease patterns should be taken into account, as models developed in other countries may not perform similarly. The researchers recommend prospective validation of AI-based cardiovascular risk models in diverse populations, including India, before their integration into routine healthcare.",
  "summary": "A recent systematic review of 30 studies published since 2017 on AI-based models developed to predict future cardiovascular disease among adults without established heart disease has highlighted the promising potential of AI in identifying individuals at risk of cardiovascular disease (CVD) earlier and enabling more personalised prevention. However, the technology is not yet ready to guide routine clinical decisions, according to researchers from the Indian Institute of Science, M.S. Ramaiah University of Applied Sciences, and the London School of Hygiene and Tropical Medicine. The review emphasizes the need for robust external validation, calibration, and assessment of clinical usefulness before AI tools can be confidently integrated into primary care or public health programmes.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 2,
    "also_reported_by": [
      {
        "outlet": "The Hindu",
        "title": "AI heart disease prediction tools show promise but are not ready for clinical use: review",
        "url": "https://urgent.news/2026/08/12/ai-heart-disease-prediction-tools-show-promise-but-are-not-ready-for-639532",
        "published": "2026-08-12T06:21:47.000Z"
      }
    ]
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}