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IntroductionVisual electrophysiology, including electroretinograms (ERG) and visual evoked potentials (VEP), provides a real-time functional assessment of retinal and post-retinal pathways, complementing structural imagi...

The integration of artificial intelligence (AI) into retinopathy of prematurity (ROP) screening represents an important advancement in neonatal ophthalmology, particularly in settings facing specialist shortages and scre...

BackgroundArtificial intelligence (AI) has substantial potential to advance periodontal and peri- implant care through novel diagnostic, prognostic, and therapeutic opportunities. Nevertheless, the evidence is scattered ...

Although vaccination remains one of the most impactful interventions in contemporary public health, with consistent and widely documented reductions in morbidity and mortality, the traditional empirical development of va...

Cardiovascular diseases remain the leading cause of mortality worldwide, making accurate and efficient imaging-based diagnosis indispensable. Modern modalities such as Coronary Computed Tomography Angiography, Cardiac Ma...

With the increasing integration of artificial intelligence (AI) across industries, there is a growing need to transform traditional teaching methods into more innovative, technology-driven, and practice-oriented approach...

Cloud computing environments face persistent structural challenges in cost control, dynamic resource allocation, and security risk management, which traditional infrastructure approaches fail to address adequately. This ...

BackgroundDelivering accurate radiation doses in heterogeneous tissues is critical in radiotherapy, yet conventional algorithms often lose accuracy in complex scenarios. Monte Carlo (MC) simulation offers a high-fidelity...

Next generation risk assessment (NGRA) demands a fundamental transformation in how toxicological test methods are validated. Traditional validation approaches, designed for animal tests and mainly for simple in vitro met...