{
  "id": 15975068,
  "title": "AI Detects Half of Lung Cancers Missed on Neck CT Scans, Highlighting New Opportunities for Medical Imaging",
  "url": "https://urgent.news/2026/10/22/ai-detects-half-of-lung-cancers-missed-on-neck-ct-scans-highlighting",
  "topic": "health",
  "section": "Health & Medicine",
  "published": "2026-10-22T00:26:51.000Z",
  "source": {
    "name": "Korea IT Times",
    "slug": "korea-it-times",
    "url": "https://www.koreaittimes.com/news/articleView.html?idxno=158413"
  },
  "original_language": "en",
  "account": "A recent study reveals that artificial intelligence may be able to detect lung cancers missed during routine CT scans performed for other medical reasons. Researchers analyzed 81,794 neck CT exams and discovered 80 cases where lung cancers were present but not documented in the initial reports. When Coreline Soft's AI software, AVIEW LCS, was applied to these cases retrospectively, it identified 41 of the cancers, yielding a sensitivity of 51.3%. The study, published in the Korean Journal of Radiology, highlights the potential for AI to uncover additional diagnostic information in medical images beyond their original purpose. This could help address blind spots in radiology workflows without needing to conduct additional imaging exams.",
  "summary": "Artificial intelligence could help identify lung cancers overlooked during routine interpretation of CT scans performed for other medical purposes, according to a new study highlighting the potential of AI to uncover additional diagnostic information from existing medical images.The findings suggest that medical imaging AI could extend beyond its original diagnostic applications, helping address…",
  "key_points": [
    "AI software AVIEW LCS detects 51.3% of lung cancers missed in neck CT scans",
    "Study analyzes 81,794 CT exams, finds 80 cancers not documented initially",
    "AI uncovers additional diagnostic information without extra imaging exams"
  ],
  "editors_take": "Automating the review of incidental imaging data turns routine diagnostic scans into proactive screening tools, reducing the need for additional exams while addressing critical blind spots in current radiology workflows.",
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "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."
}