Artificial Intelligence Medical Compendium

OBJECTIVE: Soft tissue prediction is of great importance for the surgical design and patients ' satisfaction in orthognathic surgery. Previous studies either rely on elastic mechanical models, such as finite element which involves time-consuming comp... read more 

OBJECTIVE: To develop a diagnostic model for primary Sjögren syndrome (pSS) utilizing transcriptomics-based machine learning techniques, and to explore potential therapeutic targets. METHODS: We selected patients diagnosed with pSS and control subjec... read more 

OBJECTIVE: To designe a clinical trial image medical record desensitization system based on artificial intelligence technology and to conduct preliminary applications, achieving the protection of patient privacy and promoting the safe use of clinical... read more 

AIM: To analyze research landscapes, hotspots, and trends in artificial intelligence (AI) applied to ophthalmic optical coherence tomography angiography (OCTA) from 2015 to 2024, aiming to reveal global collaborations and guide future research. METHO... read more 

INTRODUCTION: Machine learning models trained on metabolomics data frequently show reduced performance when applied to independent cohorts because of domain shifts introduced by differences in analytical platforms, sample handling, storage conditions... read more 

Gamma-linolenic acid (GLA) is a vital anti-inflammatory polyunsaturated fatty acid, yet its traditional supply from plant seeds such as evening primrose and borage is constrained by low yields and climatic instability. Consequently, microbial cell fa... read more 

Vegetation gains and losses may exhibit unequal or counterintuitive ecological responses because of differences in their initial conditions and land use transition pathways. In this study, we quantified changes in the remote sensing ecological index ... read more 

Developing a safe and effective HIV-1 vaccine remains the cornerstone of global efforts to terminate the AIDS pandemic. However, the virus's immense genetic diversity and the persistent absence of a universal Correlate of Protection (CoP) present for... read more 

OBJECTIVE: Artificial intelligence (AI) classifies routine electroencephalograms (EEGs) with expert-level accuracy, but interpretation of long-term EEG monitoring (LTM) remains reliant on time-intensive visual review. We evaluated whether autoSCORE, ... read more 

OBJECTIVE: Sexually transmitted infections (STIs) impose a heavy public health burden on low- and middle-income countries. We aimed to examine the association between female genital mutilation (FGM) and STI and develop an interpretable machine learni... read more