Artificial Intelligence Medical Compendium

BACKGROUND: Although recent advancements in artificial intelligence (AI) provide an alternative for infant motor assessment, such applications focus mainly on infants' movements within a narrow age range in a laboratory setting. This study aimed to d... read more 

The segmentation of brain tumor magnetic resonance imaging (MRI) plays a crucial role in assisting diagnosis, treatment planning, and disease progression evaluation. Convolutional neural networks (CNNs) and transformer-based methods have achieved sig... read more 

Proteins are fundamental to biological processes, mediating critical functions through precise molecular interactions. The rotational dynamics between ligand atoms and protein binding sites can significantly influence interaction efficacy by modifyin... read more 

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BACKGROUND: The incidence of total shoulder arthroplasty (TSA) has risen significantly, driven by expanded indications. This study aims to derive and validate a model for classifying patients based on the risk of short-term complications using logist... read more 

Hyperspectral imaging, as an emerging medical imaging technology, offers significant potential in biomedical research due to its ability in capturing rich spectral information. An enhanced bi-branch network integrating graph convolutional network (GC... read more 

In this paper, we examine the potential effects of relationships with Large Language Model (LLM)-based digital doppelgängers (DDs) on users' values, concerns, and interests, that is, on their practical identity. DDs are artificially intelligent conve... read more 

Gut bacterial communities play a key role in shrimp health; thus, their modulation has been a target of dietary supplements which also function in enhancing disease and stress resistance of shrimp. However, this also raised the question of whether im... read more 

OBJECTIVES: To develop a CT-based deep learning radiomics nomogram (DLRN) for the preoperative prediction of peritoneal metastasis (PM) in patients with ovarian cancer (OC). METHODS: A total of 296 patients with OCs were randomly divided into trainin... read more 

OBJECTIVE: To determine the effectiveness and cost-effectiveness of multi-gene panel sequencing compared to single-gene KRAS testing for metastatic colorectal cancer (mCRC). STUDY SETTING AND DESIGN: British Columbia, Canada (BC) is a provincial sing... read more