AI Matches Ophthalmologists in Diagnosing Corneal Infections
AI matches ophthalmologists in diagnosing corneal infections, offering accuracy and speed, a study finds, highlighting AI's potential in eye care diagnostics.
Artificial intelligence or machine learning may soon be a valuable tool for ophthalmologists in diagnosing infectious keratitis, a leading cause of corneal blindness globally. ()
What is Infectious Keratitis
Infectious keratitis is a serious eye infection that affects the cornea, the clear outer layer of the eye. It can be caused by bacteria, viruses, fungi, or parasites. Symptoms often include eye pain, redness, light sensitivity, blurred vision, and a feeling of something being in the eye. If left untreated, infectious keratitis can lead to corneal ulcers, scarring, and even blindness. It is important to seek medical attention immediately if you experience any of these symptoms.‘Did you know #artificialintelligence can now tell the difference between a healthy #eye and an infected #cornea, and even identify the type of infection? This is groundbreaking! #AI #eyecare #blindness ’
In a meta-analysis study published in eClinicalMedicine, Dr. Darren Ting from the University of Birmingham conducted a review with a global team of researchers analysing 35 studies that utilised Deep Learning (DL) models to diagnose infectious keratitis.
AI models in the study matched the diagnostic accuracy of ophthalmologists, exhibiting a sensitivity of 89.2% and specificity of 93.2%, compared to ophthalmologists' 82.2% sensitivity and 89.6% specificity.
The models in the study had analysed over 136,000 corneal images combined, and the authors say that the results further demonstrate the potential use of artificial intelligence in clinical settings.
Dr. Darren Ting, Senior author of the study, Birmingham Health Partners (BHP) Fellow and Consultant Ophthalmologist, University of Birmingham said:
"Our study shows that AI has the potential to provide fast, reliable diagnoses, which could revolutionise how we manage corneal infections globally. This is particularly promising for regions where access to specialist eye care is limited, and can help to reduce the burden of preventable blindness worldwide."
While these results highlight the potential of DL in healthcare, the study's authors emphasised the need for more diverse data and further external validation to increase the reliability of these models for clinical use.
Infectious keratitis, an inflammation of the cornea, affects millions, particularly in low- and middle-income countries where access to specialist eye care is limited. As AI technology continues to grow and play a pivotal role in medicine, it may soon become a key tool in preventing corneal blindness globally.
Reference:
- Diagnostic performance of deep learning for infectious keratitis: a systematic review and meta-analysis - (https:www.thelancet.com/journals/eclinm/article/PIIS2589-5370(24)00466-8/fulltext)