Latest AI and machine learning research in laser surgery for healthcare professionals.
BACKGROUND: Anterior segment diseases are a major global cause of preventable blindness, especially in regions with limited access to specialized ophthalmic care. Diagnosis typically requires slit-lamp biomicroscopy, creating a significant access bottleneck in primary care and rural settings. Existing AI solutions often lack the efficiency and generalizability necessary for widespread mobile deplo...
INTRODUCTION: Artificial intelligence (AI) is reshaping diagnostic paradigms across oncology. In ophthalmic oncology encompassing conditions like retinoblastoma and uveal melanoma, AI has immense potential due to the specialty's reliance on advanced imaging and the importance of early and accurate diagnosis. AREAS COVERED: This review explores recent developments in AI applications for ophthalmic ...
OBJECTIVE: This study aimed to develop and validate a predictive model incorporating early VRR slope kinetics to predict long-term treatment outcomes....
Focused ultrasound (FUS) is an emerging therapeutic and diagnostic technology in neuro-oncology, offering new strategies for molecular diagnosis, drug...
AIMS: This study evaluated the use of ophthalmic foundation deep-learning models with cross-modal transfer learning to classify multiple diseases on o...
The global demographic shift toward aging has precipitated a surge in age-related ocular pathologies, imposing a formidable public health challenge th...
PURPOSE OF REVIEW: Clinical documentation continues to expand in volume and complexity, spanning outpatient encounters, inpatient summaries, patient-p...
Autophagy is a self-digestive process in which cellular components are degraded and recycled to maintain homeostasis and cope with stress. When cells ...
Video-based or image-based human activity recognition (HAR) via machine learning algorithms helps track, detect, and categorize users' daily activitie...
OBJECTIVES: Automated segmentation of retinal blood vessels in optical coherence tomography angiography (OCTA) images is essential for early diagnosis...
Proper diagnosis of crop diseases and accurate measurement of fruit ripeness is essential in enhancing agricultural productivity, but conventional met...
BACKGROUND: The identification of reliable biomarkers for atrial fibrillation (AF) recurrence post-catheter ablation remains a clinical challenge. Thi...
Machine learning struggles with imbalanced data. Although several mitigation approaches exist, their application depends on the extent of imbalance. T...
Retinal vessel segmentation is a fundamental task in ophthalmic image analysis, playing a critical role in disease screening and clinical diagnosis. H...
Semiconductive metal oxide (SMO) gas sensors are extensively used in air monitoring, industrial safety, and hazardous-gas detection due to their high ...
BACKGROUND: Therapeutic ultrasound has emerged as a promising noninvasive or minimally invasive modality in ophthalmology, offering novel solutions ac...
With the continuous update and iteration of minimally invasive techniques, artificial intelligence and big data, the surgical treatment of early gastr...
PURPOSE: We developed MSR-UNet(Mamba-based Skip Refinement U-Net) to accurately segment the clinical target volume (CTV) and tumor bed (TB) for breast...
Tire wear particles (TWPs) are generated by mechanical abrasion of tires on road surfaces and represent a significant source of microplastic pollution...
Artificial intelligence (AI) is being increasingly used in dermatology education and research as digital health data expands and large language models...