Interpretation of artificial intelligence studies for the ophthalmologist.

Purpose Of Review: The use of artificial intelligence (AI) in ophthalmology has increased dramatically. However, interpretation of these studies can be a daunting prospect for the ophthalmologist without a background in computer or data science. This review aims to share some practical consideration...

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Publicado en:Current Opinion in Ophthalmology Vol. 31; no. 5; pp. 351 - 357
Autores principales: Tien-En Tan, Xinxing Xu, Zhaoran Wang, Yong Liu, Ting, Daniel S. W., Tan, Tien-En, Xu, Xinxing, Wang, Zhaoran, Liu, Yong
Formato: research Journal Article
Publicado: Lippincott Williams & Wilkins Sep2020
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Interpretation of artificial intelligence studies for the ophthalmologist.
      aug:
        au:
          Tien-En Tan
          Xinxing Xu
          Zhaoran Wang
          Yong Liu
          Ting, Daniel S. W.
          Tan, Tien-En
          Xu, Xinxing
          Wang, Zhaoran
          Liu, Yong
        affil: Singapore Eye Research Institute, Singapore National Eye Centre,, Singapore, Singapore
      sug:
        subj:
          Artificial Intelligence
          Data Analysis, Statistical
          Human
          Health Care Delivery
          Ophthalmology Methods
          Arthritis Impact Measurement Scales
          Impact of Events Scale
          Scales
      ab: Purpose Of Review: The use of artificial intelligence (AI) in ophthalmology has increased dramatically. However, interpretation of these studies can be a daunting prospect for the ophthalmologist without a background in computer or data science. This review aims to share some practical considerations for interpretation of AI studies in ophthalmology.Recent Findings: It can be easy to get lost in the technical details of studies involving AI. Nevertheless, it is important for clinicians to remember that the fundamental questions in interpreting these studies remain unchanged - What does this study show, and how does this affect my patients? Being guided by familiar principles like study purpose, impact, validity, and generalizability, these studies become more accessible to the ophthalmologist. Although it may not be necessary for nondomain experts to understand the exact AI technical details, we explain some broad concepts in relation to AI technical architecture and dataset management.Summary: The expansion of AI into healthcare and ophthalmology is here to stay. AI systems have made the transition from bench to bedside, and are already being applied to patient care. In this context, 'AI education' is crucial for ophthalmologists to be confident in interpretation and translation of new developments in this field to their own clinical practice.
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        Journal Article
      ougenre: Article
    language: English
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