AI to be used in more ophthalmology applications
The future of artificial intelligence looks exciting to assist but not replace ophthalmologists
Speaking during a dedicated Clinical Research Symposium on AI during the second day of the 38th Congress of the ESCRS, Béatrice Cochener-Lamard MD, PhD, outlined the development of AI in ophthalmology and the role of deep learning to assist in diagnosis, citing its successful use in diabetic retinopathy.
Looking at the latest developments, she said we are now well on the road to automatic image classification and that the use of AI will become a widespread tool in all imaging modalities (2D and 3D and beyond). Thanks to the creation of more refined algorithms, the use of ‘big data’ is not always necessary now and there are “multiple additional applications” that are on the way. These include using AI as an integrated part of “screening, diagnosis, decision support and maybe even surgical help”.
“So the future looks very exciting to help ophthalmologists for sure, but never to replace us,” Prof Cochener-Lamard concluded.
Also speaking during the session, Bruce Allan MD gave a practical presentation on the development of a machine learning accessible electronic healthcare record suitable for a patient registry.
“All machine learning data studies require the same thing; high-quality label data, usually collected for routine clinical practice,” he explained.
Data for machine learning and registry studies has four essential attributes, Dr Allan said.
“First of all, it has to be legal, in line with GDPR legislation. It has to be high quality, it has to be accessible and searchable, and it has to be secure.”Healthcare research does qualify for certain GDPR exemptions, and the data does not always have to be anonymised, rather “pseudo-anonymisation” can be sufficient, “but it useful to have clear advice about this,” Dr Allan said.
ESCRS has now commissioned legal expertise on this topic, “which should help us in each member state to know where we stand, and remove some of the obstacles”.In terms of collecting good-quality data there are some generally applicable criteria, including the use of high-quality scans with good recorded data.
“ESCRS can help by setting standards for doing this and standards for simple aspects of data acquisition, like, for example, measuring intermediate visual acuity of 63cm. These kinds of standards are not well defined at the moment,” Dr Allan said.
If storing ‘bad quality” scans, these should be labelled as such so they can be easily separated or deleted at a later date, he advised.
Also speaking during this session, Robert Wisse MD discussed the use of digital eye testing, including on smartphones, in cataract and refractive care and the use of telemonitoring.
He explained that by 2040, older people will make up half of the population in Europe, and an estimated 40% of these will have three or more chronic conditions. This will create a significant extra demand on healthcare services and strengthens the need to increasingly utilise AI and telemedicine. “A paradigm shift in healthcare delivery is needed.”
Also addressing this session, Warren Hill MD gave an update on IOL power calculation driven by AI; Renato Ambrósio MD discussed the detection of corneal ectasia using AI; while Jodhbir Mehta MD spoke about the use of AI for classification of corneal dystrophies including Fuchs’ endothelial corneal dystrophy.