Artificial intelligence (AI) use cases have been increasing in recent years, and this time, they’re already getting approvals in the medical field.
While we all know that generative AI can be used in crafting essays, emails, or even wedding vows. We also see AI check your gut health by taking pictures of your poop. This time, AI, apparently, can help doctors spot broken bones on X-rays.
The UK-based National Institute for Health and Care Excellence (NICE) has approved using four AI technologies to help doctors detect broken bones on X-rays early. This could potentially reduce the number of missed analyses during initial assessments.
NICE said that about 3 to 10 percent of broken bone cases are missed, the most common diagnostic error in emergency departments. With their approval, this £1 (~PHP 75) AI scan add-on can help UK National Health Service (NHS) doctors avoid missing fractures during early diagnosis.
This feature is an excellent addition to injury prevention, as missed fractures during the initial assessment can lead to further injury and harm to patients, making it harder for hospitals to treat in the long run. This AI feature will also reduce the need for follow-up check-ups with NHS.
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Mark Chapman, the director of HealthTech at NICE, said: “Using AI technology to help highly skilled professionals in urgent care centers to identify which of their patients has a fracture could potentially speed up diagnosis and reduce follow-up appointments needed because of a fracture missed during an initial assessment.”
Under draft guidance published by NICE, the NHS can use the four AI platforms by partnering the AI feature with a trained healthcare professional reviewing the X-ray.
The AI tools set for recommendation for use in urgent care in England are TechCare Alert, BoneView, RBfracture, or Rayvolve for children and adults aged two and up.
Application in the Philippines
As of this writing, artificial intelligence has not yet been applied to fracture detection in X-rays in Philippine hospitals. However, some studies have been conducted with promising results.
A group of researchers from UP-PGH has started a pilot study using AI and deep learning models to detect hip fractures. The study’s results concluded an accuracy of 70%, specificity of 42.2%, and sensitivity of 97.8%. However, further training will still be needed before this innovation becomes clinically useful.
Hopefully, more AI-based research with medical applications will be conducted in the Philippines to improve our healthcare at a fraction of the cost.