Publications by authors named "Lily W Y Yang"

Purpose: The COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher demand for healthcare and misinformation related to COVID-19, there is a need to explore alternative models to improve communication. Artificial Intelligence (AI) and Natural Language Processing (NLP) have emerged as promising solutions to improve healthcare delivery.

View Article and Find Full Text PDF

Background: Existing data regarding isolated tricuspid valve replacement for primary tricuspid valve disease such as infective endocarditis (IE) are limited. The aim of this study was to review our experience of isolated tricuspid valve replacement for IE.

Methods: A retrospective review was performed to evaluate the perioperative and long-term outcomes of patients undergoing isolated tricuspid valve replacement for IE at our tertiary referral center between January 2000 and December 2014.

View Article and Find Full Text PDF

Purpose: To investigate the visual outcomes and postoperative stability of IC-8 intraocular lens (AcuFocus, Inc) implantation following femtosecond laser-assisted cataract surgery.

Methods: In this prospective study, the IC-8 IOL was implanted in the non-dominant eye of 12 patients. Centration and uncorrected and corrected distance, intermediate, and near visual acuities (UDVA, UIVA, UNVA, CDVA, CIVA, CNVA) were evaluated up to postoperative month 3 (POM3).

View Article and Find Full Text PDF
Article Synopsis
  • AI is revolutionizing industries, and natural language processing (NLP) is a form of AI that helps computers understand human language, with notable potential in healthcare and ophthalmology.
  • Recent developments indicate that AI-based NLP can assist in disease screening and treatment monitoring, but successful integration relies on collaboration among different stakeholders and public acceptance.
  • For NLP systems to be widely used in healthcare, it's crucial to tackle challenges and ensure equitable access, ultimately enhancing patient care and outcomes.
View Article and Find Full Text PDF

Laser refractive surgery is one of the most commonly performed procedures worldwide. In laser refractive surgery, Femtosecond Laser in Situ Keratomileusis and Refractive Lenticule Extraction have emerged as promising alternatives to microkeratome Laser in Situ Keratomileusis and Photorefractive Keratectomy. Following laser refractive surgery, the corneal nerves, epithelial and stromal cells release neuromediators, including neurotrophins, neuropeptides and neurotransmitters.

View Article and Find Full Text PDF

Purpose: To compare long-term corneal nerve status following small incision lenticule extraction (SMILE) versus laser in situ keratomileusis (LASIK).

Methods: Twenty-four patients were randomized to receive SMILE in one eye and LASIK in the other eye. In vivo confocal microscopy examination and dry eye assessments were performed at a mean of 4.

View Article and Find Full Text PDF

Background: Enhanced recovery after surgery (ERAS) is a structured programme using a multimodal, evidence-based approach to improve post-operative outcomes. Successful implementation of ERAS can be challenging. We aimed to evaluate our initial experience with colorectal ERAS and explore the perspectives of specialist doctors and nurses.

View Article and Find Full Text PDF

Following refractive surgery, the cornea is denervated and re-innervated, hence a reproducible tool to objectively quantify this change is warranted. This study aimed to determine the repeatability and reproducibility of corneal nerve quantification between automated (ACCMetrics) and manual software (CCMetrics) following refractive surgery. A total of 1007 in vivo confocal microscopy images from 20 post-small incision lenticule extraction (SMILE) or post-laser-assisted in situ keratomileusis (LASIK) patients were evaluated by two independent observers using CCMetrics for corneal nerve fibre density (CNFD), corneal nerve branch density (CNBD), and corneal nerve fibre length (CNFL).

View Article and Find Full Text PDF

With the advancement of computational power, refinement of learning algorithms and architectures, and availability of big data, artificial intelligence (AI) technology, particularly with machine learning and deep learning, is paving the way for 'intelligent' healthcare systems. AI-related research in ophthalmology previously focused on the screening and diagnosis of posterior segment diseases, particularly diabetic retinopathy, age-related macular degeneration and glaucoma. There is now emerging evidence demonstrating the application of AI to the diagnosis and management of a variety of anterior segment conditions.

View Article and Find Full Text PDF