{
  "id": 1805303,
  "title": "How can AI help identify pain when animals can't tell us they're suffering?",
  "url": "https://urgent.news/2026/08/18/how-can-ai-help-identify-pain-when-animals-cant-tell-us-theyre",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-18T21:30:04.000Z",
  "source": {
    "name": "Phys.org",
    "slug": "phys-org",
    "url": "https://phys.org/news/2026-08-ai-pain-animals-theyre.html"
  },
  "original_language": "en",
  "account": "A groundbreaking AI framework called SHIC-XE has been developed to detect pain in horses from video analysis, providing stable, anatomically consistent explanations for its decisions. This framework, created by an international team of researchers led by Dr. Marcelo Feighelstein from Tel-Hai University's Artificial Intelligence Systems Engineering Program, addresses the challenge of identifying pain in animals who cannot communicate their suffering. By using facial expressions, body language, and movement patterns, SHIC-XE interprets signs of pain in horses, offering a technological voice to those who have no words. The AI's explanations are quantitatively comparable to expert assessments, marking a significant breakthrough in explainable artificial intelligence. SHIC-XE achieves strong performance across various clinical scenarios, with F1 scores ranging from 0.67 to 0.80, indicating high accuracy and reliability in detecting pain from video. The system highlights anatomically relevant regions when making decisions, bringing researchers closer to understanding and validating AI's reasoning. While initially developed for equine pain recognition, the implications of SHIC-XE extend to human healthcare, offering potential applications in pain assessment for newborns, sedated patients, dementia patients, and neurological movement disorders. This development not only transforms technology into a reliable partner in care but also represents a crucial step toward trustworthy AI systems in real-world clinical and health environments.",
  "summary": "A new AI framework, known as SHIC-XE, has been developed to detect signs of pain in horses from video analysis while providing stable, anatomically consistent explanations for its decisions. The framework was developed by an international team of researchers led by Dr. Marcelo Feighelstein, head of the Artificial Intelligence Systems Engineering Program at Tel-Hai University's new Cluster of…",
  "key_points": [],
  "editors_take": null,
  "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."
}