Kristina Šulinskaitė, Daiva Zagurskienė, Aurelija Blaževičienė
Patients' health literacy and health behaviour assessment in primary health care: evidence from a cross-sectional survey
BMC primary care
significant contributor blindness visual impairment globally uncorrected refractive error plan effective interventions eye care professionals must promptly identify people high risk acquiring myopia monitor disease progress artificial intelligence ai machine learning ml enormous potential improve diagnosis treatment systematic review explores current state ml ai applications diagnoses treatment refractory errors optometry systematic review metaanalysis studies evaluating diagnostic performance aibased tools pubmed conducted according preferred reporting items systematic reviews metaanalyses prisma guidelines find relevant studies use ml ai diagnosis treatment refractive errors optometry thorough search conducted various electronic databases pubmed google scholar web science search limited studies published january 2015 december 2022 search terms used refractive errors myopia optometry machine learning ophthalmology artificial intelligence total nine studies met inclusion criteria included final analysis ml increasingly utilized automating clinical data processing ai technology progresses making formerly laborintensive work possible ai models primarily use neural network demonstrated exceptional efficiency performance analysis vast medical data rivaling boardcertified healthcare professionals several studies showed ml models could support diagnosis clinical decisionmaking moreover ml algorithm predicted future refraction values patients myopia ai ml models great potential improve diagnosis treatment refractive errors optometry