Artificial Intelligence Medical Compendium

Recently, convolutional neural networks (CNNs) have made significant strides in hyperspectral image classification (HSIC) tasks by contextualizing the convolutional kernels as global as possible. However, as the kernel sizes increase, encoding multi-... read more 

Multivariate time series (MTS) forecasting plays a pivotal role in the digitalization and intelligent development of modern society, while previous MTS forecasting methods based on deep learning often rely on capturing intra-series dependencies for m... read more 

Deploying Deep Learning algorithms in the real world requires some care that is generally not considered in the training procedure. In real-world scenarios, where the input data cannot be controlled, it is important for a model to identify when a sam... read more 

UTIs are regarded as the second most prevalent global problem, with 150 to 250 million cases reported annually. Poor hygiene, anatomical abnormalities, and catheterization are the leading causes. Most UTI cases are caused by Escherichia coli and othe... read more 

Lung cancer is a severe and life-threatening type of cancer that originates in the lung tissues. Computed Tomography (CT) image emerges as the primary diagnostic tool for identifying lung cancer. However, manual interpretation of CT images necessitat... read more 

This study aims to develop a multimodal driver emotion recognition system that accurately identifies a driver's emotional state during the driving process by integrating facial expressions, ElectroCardioGram (ECG) and ElectroEncephaloGram (EEG) signa... read more 

BACKGROUND: Spasticity is a common consequence of upper motor neuron syndrome, affecting approximately 42.6% of stroke patients and impairing quality of life. Although stretching is widely used, the optimal type and parameters remain unclear. OBJECTI... read more 

AIM: This study aimed to validate the mediating role of nurses' AI trust in the relationship between AI uncertainties and AI competence. DESIGN: A cross-sectional study. METHODS: A purposive sample of 550 registered nurses with at least 1 year of cli... read more 

Genetic algorithms (GAs) are quantitative optimization techniques that have exclusively been utilized for scale abbreviation despite their potential application to new scale development. Here, we modeled the trait constructs of the triarchic psychopa... read more 

OBJECTIVE: Researchers in otolaryngology-head and neck surgery (OHNS) have sought to explore the potential of large language models (LLMs), but many publications do not include crucial information, such as prompting approach and model parameters. Thi... read more