Artificial Intelligence Medical Compendium

OBJECTIVE: This study aims to optimize depression screening tools through a data-driven approach, identifying the most predictive core item combination from the PHQ-9 scale to construct a new simplified depression screening tool. METHODS: Using 11 in... read more 

Biomass elemental and biochemical compositions determine its conversion behavior and utilization potential. However, a standardized classification system based on these intrinsic characteristics is lacking, and different biomass types follow distinct... read more 

In deep learning, the robustness and generalizability of models significantly depend on diverse and heterogeneous training data. Acquiring such an extensive dataset is challenging in fields like disorder prediction due to data scarcity, which can be ... read more 

UNLABELLED: Hematopoietic stem cell (HSC) mobilization is a critical step in bone marrow transplantation for treating hematological malignancies and other disorders. Since poor mobilization affects 10–20% of patients, it can cause failure of the tran... read more 

OBJECTIVES: This research aimed to investigate how different image processing techniques influence the performance of a deep learning model in classifying cervical vertebral maturation (CVM) stages. METHODS: A dataset of 799 cephalometric radiographs... read more 

OBJECTIVES: Lupus nephritis (LN) is one of the most common complications of systemic lupus erythematosus. This study aimed to identify key autophagy-related genes and to provide a novel approach for the diagnosis and treatment of LN. METHODS: Gene ex... read more 

OBJECTIVE: Accurate classification of salivary gland tumors is critical to guiding appropriate management. This study evaluates the diagnostic performance of artificial intelligence models in classifying salivary gland tumors on ultrasound. DATA SOUR... read more 

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OBJECTIVE: To evaluate the performance of convolutional neural network (CNN)-based models for predicting fetal rabbit lung development: unimodal models using B-mode and shear wave elastography (SWE) and a multimodal model combining B-mode and SWE. ME... read more 

PURPOSE: To develop and validate a rapid, fully automated method for shimming of the lung. METHODS: For field mapping of the lung, a custom 2D RF spoiled gradient echo sequence was used offering sub-millisecond echo times. At 3T, four echo-shifted co... read more