Privacy-Preserving Technology Using Federated Learning and Blockchain in Protecting against Adversarial Attacks for Retinal Imaging.

Purpose: Collaboration provides valuable data for robust artificial intelligence (AI) model development. Federated learning (FL) is a privacy-enhancing technology that allows collaboration while respecting privacy via the development of models without raw data transfer. However state-of-the-art FL models still face challenges in non-independent and identically distributed (non-IID) health care settings and remain susceptible to privacy breaches.

Evaluation of Visual Outcomes in Patients With Aberrated Corneas Implanted With the IC-8 Small-Aperture IOL.

Purpose: To assess the visual outcomes in patients with cataract implanted with a small-aperture intraocular lens (IOL) in eyes with aberrated corneas.

Methods: This prospective, non-interventional, single-center clinical study was conducted at Singapore National Eye Centre, Singapore. Twenty-one patients with aberrated corneas had IC-8 IOL (Bausch & Lomb, Inc) implantation.

Cybersecurity in the generative artificial intelligence era.

Generative Artificial Intelligence (GenAI) are algorithms capable of generating original content. The ability of GenAI to learn and generate novel outputs alike human cognition has taken the world by storm and ushered in a new era. In this review, we explore the role of GenAI in healthcare, including clinical, operational, and research applications, and delve into the cybersecurity risks of this technology.

Clinical performance of automated machine learning: A systematic review.

Introduction: Automated machine learning (autoML) removes technical and technological barriers to building artificial intelligence models. We aimed to summarise the clinical applications of autoML, assess the capabilities of utilised platforms, evaluate the quality of the evidence trialling autoML, and gauge the performance of autoML platforms relative to conventionally developed models, as well as each other.

Method: This review adhered to a prospectively registered protocol (PROSPERO identifier CRD42022344427).

Femtosecond laser-assisted in situ keratomileusis versus small-incision lenticule extraction: current approach based on evidence.

Purpose Of Review: Laser keratorefractive surgery achieves excellent visual outcomes for refractive error correction. With femtosecond laser, small incision lenticule extraction (SMILE) is an increasingly viable alternative to laser-assisted in situ keratomileusis (LASIK). Comparative studies demonstrate similar efficacy and predictability between SMILE and LASIK, making it difficult for clinicians to choose which to use.

Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture.

Federated learning (FL) is a distributed machine learning framework that is gaining traction in view of increasing health data privacy protection needs. By conducting a systematic review of FL applications in healthcare, we identify relevant articles in scientific, engineering, and medical journals in English up to August 31st, 2023. Out of a total of 22,693 articles under review, 612 articles are included in the final analysis.

Continuity obstetric care demonstrates greater vaginal birth after caesarean success.

Background: Australia's caesarean rate is higher than Organisation for Economic Co-operation and Development (OECD) average, and is rising. Vaginal birth after caesarean (VBAC) is safe for selected women. Midwifery continuity of care (CoC) is associated with higher rates of vaginal birth compared to other models; however, impacts on VBAC attempts and success are unknown.

International incidence and temporal trends for rhegmatogenous retinal detachment: A systematic review and meta-analysis.

We set out to estimate the international incidence of rhegmatogenous retinal detachment (RRD) and to evaluate its temporal trend over time. There is a lack of robust estimates on the worldwide incidence and trend for RRD, a major cause of acute vision loss. We conducted a systematic review of RRD incidence.

A translational perspective towards clinical AI fairness.

Artificial intelligence (AI) has demonstrated the ability to extract insights from data, but the fairness of such data-driven insights remains a concern in high-stakes fields. Despite extensive developments, issues of AI fairness in clinical contexts have not been adequately addressed. A fair model is normally expected to perform equally across subgroups defined by sensitive variables (e.

Federated and distributed learning applications for electronic health records and structured medical data: a scoping review.

Objectives: Federated learning (FL) has gained popularity in clinical research in recent years to facilitate privacy-preserving collaboration. Structured data, one of the most prevalent forms of clinical data, has experienced significant growth in volume concurrently, notably with the widespread adoption of electronic health records in clinical practice. This review examines FL applications on structured medical data, identifies contemporary limitations, and discusses potential innovations.

Artificial intelligence and digital health in global eye health: opportunities and challenges.

Global eye health is defined as the degree to which vision, ocular health, and function are maximised worldwide, thereby optimising overall wellbeing and quality of life. Improving eye health is a global priority as a key to unlocking human potential by reducing the morbidity burden of disease, increasing productivity, and supporting access to education. Although extraordinary progress fuelled by global eye health initiatives has been made over the last decade, there remain substantial challenges impeding further progress.

Six-Year Incidence and Risk Factors for Primary Open-Angle Glaucoma and Ocular Hypertension: The Singapore Epidemiology of Eye Diseases Study.

Objective: To determine the incidence and risk factors for primary open-angle glaucoma (POAG) and ocular hypertension (OHT) in a multiethnic Asian population.

Design: Population-based cohort study.

Participants: The Singapore Epidemiology of Eye Diseases study included 10 033 participants in the baseline examination between 2004 and 2011.

Explainable artificial intelligence in ophthalmology.

Purpose Of Review: Despite the growing scope of artificial intelligence (AI) and deep learning (DL) applications in the field of ophthalmology, most have yet to reach clinical adoption. Beyond model performance metrics, there has been an increasing emphasis on the need for explainability of proposed DL models.

Recent Findings: Several explainable AI (XAI) methods have been proposed, and increasingly applied in ophthalmological DL applications, predominantly in medical imaging analysis tasks.

Artificial intelligence enabled smart digital eye wearables.

Purpose Of Review: Smart eyewear is a head-worn wearable device that is evolving as the next phase of ubiquitous wearables. Although their applications in healthcare are being explored, they have the potential to revolutionize teleophthalmology care. This review highlights their applications in ophthalmology care and discusses future scope.

Artificial intelligence innovation in healthcare: Relevance of reporting guidelines for clinical translation from bench to bedside.

Artificial intelligence (AI) and digital innovation are transforming healthcare. Technologies such as machine learning in image analysis, natural language processing in medical chatbots and electronic medical record extraction have the potential to improve screening, diagnostics and prognostication, leading to precision medicine and preventive health. However, it is crucial to ensure that AI research is conducted with scientific rigour to facilitate clinical implementation.

Metaverse and Virtual Health Care in Ophthalmology: Opportunities and Challenges.

The outbreak of the coronavirus disease 2019 has further increased the urgent need for digital transformation within the health care settings, with the use of artificial intelligence/deep learning, internet of things, telecommunication network/virtual platform, and blockchain. The recent advent of metaverse, an interconnected online universe, with the synergistic combination of augmented, virtual, and mixed reality described several years ago, presents a new era of immersive and real-time experiences to enhance human-to-human social interaction and connection. In health care and ophthalmology, the creation of virtual environment with three-dimensional (3D) space and avatar, could be particularly useful in patient-fronting platforms (eg, telemedicine platforms), operational uses (eg, meeting organization), digital education (eg, simulated medical and surgical education), diagnostics, and therapeutics.