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Meibomian gland dysfunction (MGD) is increasingly recognized as a critical contributor to evaporative dry eye, significantly impacting visual quality. With a global prevalence estimated at 35.8 %, it presents substantial challenges for clinicians. Conventional manual evaluation techniques for MGD face limitations characterized by inefficiencies, high subjectivity, limited big data processing capabilities, and a dearth of quantitative analytical tools. With rapidly advancing artificial intelligence (AI) techniques revolutionizing ophthalmology, studies are now leveraging sophisticated AI methodologies--including computer vision, unsupervised learning, and supervised learning--to facilitate comprehensive analyses of meibomian gland (MG) evaluations. These evaluations employ various techniques, including slit lamp examination, infrared imaging, confocal microscopy, and optical coherence tomography. This paradigm shift promises enhanced accuracy and consistency in disease evaluation and severity classification. While AI has achieved preliminary strides in meibomian gland evaluation, ongoing advancements in system development and clinical validation are imperative. We review the evolution of MG evaluation, juxtapose AI-driven methods with traditional approaches, elucidate the specific roles of diverse AI technologies, and explore their practical applications using various evaluation techniques. Moreover, we delve into critical considerations for the clinical deployment of AI technologies and envisages future prospects, providing novel insights into MG evaluation and fostering technological and clinical progress in this arena. [ABSTRACT FROM AUTHOR]

We compare multifocal intraocular lenses (MFIOLs) to monofocal IOLs for visual acuity (VA), contrast sensitivity, and adverse events using data from 21 randomized controlled trials with 2951 subjects. There was no statistical difference between uncorrected distance VA and corrected distance VA. Compared with monofocal IOLs, MFIOLs showed a better performance on uncorrected intermediate VA measured at 60 cm and uncorrected near VA; the mean differences were -0.06 (95% confidence interval [CI]: -0.10, -0.03) and -0.13 (95% CI: -0.20, -0.07). Distance-corrected intermediate VA and distance-corrected near VA were measured wearing distance correction. MFIOLs performed better than monofocal IOLs on distance-corrected intermediate VA at 60 cm and distance-corrected near VA; the mean differences were -0.09 (95% CI: -0.12, -0.06) and -0.31 (95% CI: -0.43, -0.19). The contrast sensitivity of the MFIOL group was lower than that of the monofocal IOL group; mean difference was -0.06 (95% CI: -0.11, -0.02). More patients were spectacle free in the MFIOL group; the risk ratio was 2.86 (95% CI: 1.73, 4.73). More patients were troubled by glare and halos in the MFIOL group; the risk ratios were 1.91 (95% CI: 1.24, 2.95) and 3.08 (95% CI: 2.11, 4.49). We conclude that, compared with monofocal IOLs, MFIOLs give patients better near vision and intermediate vision at 60 cm, both corrected and uncorrected. Patients undergoing MFIOLs implantation are more likely to be spectacle free but have a higher risk of glare, halos, and lower contrast sensitivity. [ABSTRACT FROM AUTHOR]