INTRODUCTION: Lung cancer is the leading cause of cancer-related deaths worldwide, emphasizing the need for early and accurate diagnosis. Precise segmentation of lung regions and tumors in imaging is critical for effective diagnosis and treatment. Th... read more
This scoping review aimed to map the available evidence on deep learning (DL) models for predicting early-onset preeclampsia (EOPE), focusing on both clinical and imaging-based approaches. A comprehensive search of five databases identified 15 eligib... read more
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Apr 3, 2026
BACKGROUND: Surgical decisions for severe traumatic brain injury (TBI) are often made under prognostic uncertainty. Existing prognostic models predict overall outcomes but do not estimate how an individual's outcome might change with the decision to ... read more
AIM: This study aimed to investigate the relationship between pediatric nurses' levels of artificial intelligence literacy and artificial intelligence anxiety. METHODS: The study population consisted of 246 nurses working at children hospital within ... read more
INTRODUCTION: Acne vulgaris is a prevalent dermatological disorder that affects millions worldwide, causing both physical discomfort and psychological burden. Conventional therapies often provide limited benefit due to poor skin permeability and tole... read more
Recent vision-language models (VLMs) typically rely on a single vision encoder trained with contrastive image-text objectives, such as CLIP-style pretraining. While contrastive encoders are effective for cross-modal alignment and retrieval, self-supe... read more
Most of the recent generative image super-resolution (SR) methods rely on adapting large text-to-image (T2I) diffusion models pretrained on web-scale text-image data. While effective, this paradigm starts from a generic T2I generator, despite that SR... read more
Non-contrast chest CTs offer a rich opportunity for both conventional pulmonary and opportunistic extra-pulmonary screening. While Multi-Task Learning (MTL) can unify these diverse tasks, standard hard-parameter sharing approaches are often suboptima... read more
The rapid adoption of the Internet of Medical Things (IoMT) is transforming healthcare by enabling seamless connectivity among medical devices, systems, and services. However, it also introduces serious cybersecurity and patient safety concerns as at... read more
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