How Artificial Intelligence Algorithms Can Detect Cataract

The use of AI in healthcare has new, exciting applications such as cataract detection that can help in early and accurate detection in a cost-effective way.

A cataract is a major issue faced by people all over the world. In fact, it is the leading cause of blindness across the globe. In the United States of America alone, cataract affects about twenty million people in the age group of 40 and above. This number is expected to increase in the upcoming years.

While cataracts can be dealt with using surgery, the major hurdle lies in detecting cataracts. Firstly, the methods used in cataract detection are not highly efficient. Secondly, there is a lack of medical experts that can detect cataracts correctly for a large volume of the population.

Researchers around the globe are now turning to AI algorithms to detect cataracts efficiently and quickly and stop people from going blind. This use of AI in healthcare is not new. It is already helping in various processes like disease detection, treatments, surgeries, and patient recoveries. So, how will AI help in cataract detection? Let’s find out.

Using AI in Cataract Detection

Currently, cataract detection is done by using a slit-lamp microscope or ophthalmoscope. This process requires highly experienced professionals, which poses a huge challenge, especially in poor or developing countries, where there is a shortage of experienced ophthalmologists.

However, this problem can be dealt with easily using AI algorithms. The algorithms have been trained on datasets using slit-lamp or color fundus photographs from previously conducted examinations. The algorithms analyze the photos to identify common patterns with cataract patients. They can then use this information for automated detection and grading of cataracts quickly and accurately. Moreover, the cameras used in cataract detection using AI models make use of low-cost NIR cameras in place of costly ophthalmoscopes, which helps bring the costs down. 

For example, Jin Rang et al. developed a deep Convoluted Neural Network that achieved an AUC of 97.04%, a sensitivity of 97.26%, and a specificity of 96.92% for detecting cataracts using fundus images. Similarly, other AI algorithms are being developed by researchers across the globe for cataract detection.

The Growing Role of AI in Healthcare With Cataract

The use of AI in healthcare for cataracts is not limited to detection. It can also be used to streamline cataract surgeries too. For example, AI algorithms can be used to augment surgical skill training for inexperienced ophthalmologists by identifying the different phases of surgeries on video. They can also be used to optimize operation theatre procedures. This is possible due to the accurate prediction of the surgery duration by AI models.

The use of AI in healthcare for cataract detection can help solve a major problem. AI algorithms will not only simplify cataract detection but will also help optimize treatments and bring their costs down significantly.