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Artificial Intelligence to Speed Up Diagnosis of Eye Diseases

Artificial Intelligence to Speed Up Diagnosis of Eye Diseases

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  • Using artificial intelligence (AI) and machine learning a new computational tool was developed that can screen patients for eye diseases.
  • AI-based system was trained using non-invasive eye scans conducted with optical coherence tomography.
  • The machine could tell if a patient should be referred for treatment within 30 seconds, with more than 95% accuracy.

A new computational tool that can screen eye diseases efficiently was developed using artificial intelligence and machine learning techniques. The tool developed by research teams at Shiley Eye Institute at UC San Diego Health and University of California San Diego School of Medicine, with colleagues in China, Germany and Texas, could potentially speed up the diagnosis and eventually treatment of common but blinding eye diseases. The study is published in the journal Cell.

Artificial intelligence (AI) is a technology of the future with immense potential in all fields including medicine. Today, in its early stages the approach is laborious, expensive, and requires using millions of data to train an AI system. However, the new study has developed a feasible and efficient way of training the AI system.


"Artificial intelligence has huge potential to revolutionize disease diagnosis and management by doing analyses and classifications involving immense amounts of data that are difficult for human experts - and doing them rapidly," said senior author Kang Zhang, MD, PhD, professor of ophthalmology at Shiley Eye Institute and founding director of the Institute for Genomic Medicine at UC San Diego School of Medicine.

The AI-based neural network was developed using a technique called transfer learning. Here the knowledge gained in solving one problem is stored by a computer and applied to different but related problems.

For example, if an AI neural network optimized to recognize anatomical parts of the eye like the retina or the cornea, the system can more quickly and efficiently identify and evaluate these structures when examining images of a whole eye. This allows the system to learn effectively with a much smaller dataset.

The Efficiency of the AI-based System

This study was primarily focused on using the new tool to diagnose two common causes of irreversible blindness: macular degeneration and diabetic macular edema, both if detected early are treatable.

The AI-based tool's diagnoses of eye scans were compared with diagnoses from five ophthalmologists who reviewed the same scans. The machine was found to perform alike any well-trained ophthalmologist. The machine could decide if a patient should be referred for treatment within 30 seconds and that too with a 95% accuracy.

Apart from eye diseases, the AI tool was also used to diagnose childhood pneumonia. Based on the chest X-rays, the system could differentiate between viral and bacterial pneumonia with greater than 90 percent accuracy.

The new approach has great potential in early detection of diseases, which ultimately leads to early treatment. The AI-based system is also a great resource for regions with a scarcity of medical professionals and testing centers.

References :
  1. Artificial intelligence quickly and accurately diagnoses eye diseases and pneumonia - (https://www.eurekalert.org/emb_releases/2018-02/uoc--aiq021518.php)
  2. Cell, Kermany et al. "Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning." Cell, (2018) DOI: 10.1016/j.cell.2018.02.010
Source: Medindia

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