Latest AI and machine learning research in menopause for healthcare professionals.
Large Language Models (LLMs) have demonstrated great potential for conducting diagnostic conversations but evaluation has been largely limited to language-only interactions, deviating from the real-world requirements of remote care delivery. Instant messaging platforms permit clinicians and patients to upload and discuss multimodal medical artifacts seamlessly in medical consultation, but the ab...
The purpose of this study is to systematically review and evaluate the accuracy of low-dose chest CT-based artificial intelligence in osteoporosis screening. A systematic literature search for relevant studies up to 13th December 2024 was performed in the PubMed, Scopus, Web of Science, and Cochrane Library databases. This meta-analysis was conducted in accordance with the PRISMA-DTA statement. Mo...
A clustered adaptive intervention (cAI) is a pre-specified sequence of decision rules that guides practitioners on how best - and based on which mea...
We investigate the role of large language models (LLMs) in supporting mental health by analyzing Reddit posts and comments about mental health conve...
Skin, the primary regulator of heat exchange, relies on sweat glands for thermoregulation. Alterations in sweat gland morphology play a crucial role...
Hyperspectral image (HSI) classification has been one of the hot topics in remote sensing fields. Recently, the Mamba architecture based on selectiv...
Surrogate markers are most commonly studied within the context of randomized clinical trials. However, the need for alternative outcomes extends bey...
We introduce CrossWKV, a novel cross-attention mechanism for the state-based RWKV-7 model, designed to enhance the expressive power of text-to-image...
The advancement of AI systems for mental health support is hindered by limited access to therapeutic conversation data, particularly for trauma trea...
Automated extraction of chemical structures and their bioactivity data is crucial for accelerating drug discovery and enabling data-driven pharmaceu...
Accommodating edge networks between IoT devices and the cloud server in Hierarchical Federated Learning (HFL) enhances communication efficiency with...
Clinical document classification is essential for converting unstructured medical texts into standardised ICD-10 diagnoses, yet it faces challenges ...
OBJECTIVE: This study aims to develop and validate a machine learning model for identifying individuals within the nursing population experiencing sev...
BACKGROUND: Age-related conditions, such as osteoporosis and sarcopenia, alongside chronic diseases, can result in significant musculoskeletal tissue ...
Free tensors are tensors which, after a change of bases, have free support: any two distinct elements of its support differ in at least two coordina...
Introduction: Bone health disorders like osteoarthritis and osteoporosis pose major global health challenges, often leading to delayed diagnoses due...
Masked Generative Image Transformers (MaskGIT) have emerged as a scalable and efficient image generation framework, able to deliver high-quality vis...
Reasoning capabilities have significantly improved the performance of vision-language models (VLMs) in domains such as mathematical problem-solving,...
The integration of Rotary Position Embedding (RoPE) in Multimodal Diffusion Transformer (MMDiT) has significantly enhanced text-to-image generation ...
In the real world, users always have multiple interests while surfing different services to enrich their daily lives, e.g., watching hot short video...