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1.
Ophthalmic Plast Reconstr Surg ; 40(3): 303-311, 2024.
Article in English | MEDLINE | ID: mdl-38215452

ABSTRACT

PURPOSE: This study evaluates and compares the accuracy of responses from 2 artificial intelligence platforms to patients' oculoplastics-related questions. METHODS: Questions directed toward oculoplastic surgeons were collected, rephrased, and input independently into ChatGPT-3.5 and BARD chatbots, using the prompt: "As an oculoplastic surgeon, how can I respond to my patient's question?." Responses were independently evaluated by 4 experienced oculoplastic specialists as comprehensive, correct but inadequate, mixed correct and incorrect/outdated data, and completely incorrect. Additionally, the empathy level, length, and automated readability index of the responses were assessed. RESULTS: A total of 112 patient questions underwent evaluation. The rates of comprehensive, correct but inadequate, mixed, and completely incorrect answers for ChatGPT were 71.4%, 12.9%, 10.5%, and 5.1%, respectively, compared with 53.1%, 18.3%, 18.1%, and 10.5%, respectively, for BARD. ChatGPT showed more empathy (48.9%) than BARD (13.2%). All graders found that ChatGPT outperformed BARD in question categories of postoperative healing, medical eye conditions, and medications. Categorizing questions by anatomy, ChatGPT excelled in answering lacrimal questions (83.8%), while BARD performed best in the eyelid group (60.4%). ChatGPT's answers were longer and potentially more challenging to comprehend than BARD's. CONCLUSION: This study emphasizes the promising role of artificial intelligence-powered chatbots in oculoplastic patient education and support. With continued development, these chatbots may potentially assist physicians and offer patients accurate information, ultimately contributing to improved patient care while alleviating surgeon burnout. However, it is crucial to highlight that artificial intelligence may be good at answering questions, but physician oversight remains essential to ensure the highest standard of care and address complex medical cases.


Subject(s)
Artificial Intelligence , Humans , Ophthalmologic Surgical Procedures/methods , Surveys and Questionnaires
2.
Genes (Basel) ; 14(2)2023 02 15.
Article in English | MEDLINE | ID: mdl-36833424

ABSTRACT

Spondyloocular syndrome (SOS, OMIM # 605822) is a rare genetic disorder characterized by osseous and ocular manifestations, including generalized osteoporosis, multiple long bones fractures, platyspondyly, dense cataracts and retinal detachment, and dysmorphic facial features, with or without short stature, cardiopathy, hearing impairment, and intellectual disability. Biallelic mutations in the XYLT2 gene (OMIM * 608125), encoding the xylosyltransferase II, were shown to be responsible for this disease. To date, 22 cases with SOS have been described, with varying clinical presentations and a yet-to-be-established genotypic-phenotypic correlation. Two patients from a consanguineous Lebanese family that presented with SOS were included in this study. Whole exome sequencing revealed a novel homozygous nonsense mutation in XYLT2 (p.Tyr414*) in these patients. We review all previously reported cases with SOS, describe the second nonsense mutation in XYLT2, and contribute to a better delineation of the phenotypic spectrum of the disease.


Subject(s)
Osteochondrodysplasias , Osteoporosis , Humans , Codon, Nonsense , Phenotype , Osteochondrodysplasias/genetics , Homozygote , Osteoporosis/genetics , Vision Disorders
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