Artificial Intelligence Medical Compendium

Breast cancer is the most commonly diagnosed cancer among women worldwide, and concerns regarding radiation exposure from mammography screening remain a potential barrier to participation. This scoping review explores existing models estimating long-... read more 

OBJECTIVE: Eating disorder (ED) history may impact mother-child communication during mealtimes and contribute to transgenerational transmission of ED. This study employed machine learning (ML) to identify speech characteristics during mother-child fe... read more 

OBJECTIVES: The aim of this study was to develop a machine-learning model to assist in treatment decision-making for surgery, camouflage, and growth modulation in Class II malocclusion patients and to evaluate its validity and reliability. MATERIAL A... read more 

INTRODUCTION: The objective of this study was to assess the repeatability of orthodontic responses generated by multiple large language models across repeated time points. METHODS: This experimental study assessed the answers provided by ChatGPT-3.5,... read more 

We develop new uncertainty propagation methods for feed-forward neural network architectures with leaky ReLU activation functions subject to random perturbations in the input vectors. In particular, we derive analytical expressions for the probabilit... read more 

Although Deep Learning (DL)-based Medical Image Segmentation (MIS) models are critically important, adversarial attacks substantially diminish their efficacy. Such attacks subtly perturb inputs, causing the model to produce inaccurate predictions. Th... read more 

Lead (Pb), a heavy metal with extensive industrial applications, poses significant risks to human health and the environment. These detrimental effects have driven strict global and local regulations, such as World Health Organization and Taiwan's dr... read more 

Driven by the dual imperatives of global food security and agricultural sustainability, dynamic plant nitrogen monitoring technology has emerged as a research focus in precision agriculture. This technology represents a critical breakthrough over tra... read more 

Next Basket Recommendation (NBR) aims to predict the items in the next basket a user will interact with, based on the user's basket interaction history. However, data sparsity has been a significant challenge in this area. Contrastive Learning (CL) l... read more 

Incomplete multi-view clustering (IMVC) has become an area of increasing focus due to the frequent occurrence of missing views in real-world multi-view datasets. Traditional methods often address this by attempting to recover the missing views before... read more