Publications by authors named "D R O'Boyle"

Article Synopsis
  • The study aimed to validate a prediction algorithm that identifies infants at risk of hypoxic ischemic encephalopathy (HIE) right after birth using basic clinical data.
  • Conducted at a tertiary maternity hospital, it analyzed electronic health records of 1,081 term infants born from January 2017 to December 2021, focusing on key clinical factors like Apgar scores and postnatal pH.
  • The results showed that the random forest model achieved the highest accuracy in predicting HIE, correctly classifying 86.5% of infants, highlighting the potential for this machine learning tool to facilitate timely medical interventions.
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Purpose: To estimate the incidence of neodymium-doped yttrium aluminum garnet laser (Nd:YAG) capsulotomy up to five years after cataract surgery with different single-piece acrylic monofocal IOLs in a Spanish cohort.

Patients And Methods: Data were extracted from electronic medical records. Eligible participants were aged ≥65, had cataract surgery with one of five different acrylic monofocal IOLs (Alcon AcrySof, AJL LLASY60, Medicontur Bi-flex, IOL Tech Stabibag and Zeiss Asphina), and more than six months baseline data.

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Purpose: Occupational musculoskeletal disorders are prevalent in ophthalmic surgeons and can impact surgeons' well-being and productivity. Heads-up displays may reduce ergonomic stress compared to conventional microscopes. This cross-sectional, non-interventional study compared ergonomic experience between heads-up display and conventional ocular microscopes.

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Background: There are no early, accurate, scalable methods for identifying infants at high risk of poor cognitive outcomes in childhood. We aim to develop an explainable predictive model, using machine learning and population-based cohort data, for this purpose.

Methods: Data were from 8858 participants in the Growing Up in Ireland cohort, a nationally representative study of infants and their primary caregivers (PCGs).

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Purpose: Inefficiencies from manual data entry and non-integration exist throughout the cataract surgery workflow. The aim of this study was to evaluate the impact of SMARTCataract, an innovative cloud-based digital surgical planning platform (SPS) on efficiency in preoperative (diagnostic workup, surgery planning), intraoperative, and postoperative phases of cataract surgery. The primary objective aimed to assess time and number of manual transcription data points (TPs) required for all pre-, intra-, and postoperative devices that integrate with the SPS and surgery planning time across three patient types (post-refractive, astigmatic, conventional).

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