Artificial Intelligence Medical Compendium

Convolutional neural network (CNN) has been widely used to undertake the task of image classification. Unfortunately, the implicit decision knowledge carried by a trained CNN model is often difficult to be comprehended by humans. A feasible method to... read more 

BACKGROUND: Lymph node metastasis (LNM) is a critical prognostic indicator in papillary thyroid carcinoma (PTC), significantly influencing surgical decision-making and the administration of adjuvant therapies. While conventional imaging modalities su... read more 

OBJECTIVE: To investigate the temporal evolution and predictive value of individual histopathological features of oral epithelial dysplasia (OED) during carcinogenesis, and to evaluate the diagnostic utility of optical fluorescence imaging in a murin... read more 

Pretrained large models (PLMs), such as ChatGPT, have demonstrated remarkable performance across diverse tasks. However, the significant computational requirements of PLMs have discouraged most product teams from running or fine-tuning them. In such ... read more 

Biomarker research in psychopathology increasingly employs high-dimensional Omics approaches. Yet, proteomics based on human hair remain largely unexplored, despite its potential to efficiently capture stable biological signals accumulated over weeks... read more 

Deep reinforcement learning (DRL) has been applied to real-time control (RTC) of urban drainage systems (UDSs), with impressive performance and efficiency in reducing urban flooding and combined sewer overflows (CSO). However, for complex UDSs, learn... read more 

BACKGROUND AND OBJECTIVE: Three-dimensional (3D) tumor spheroids are widely adopted in preclinical drug screening for their ability to mimic the complexity of in vivo tumor microenvironments. Nevertheless, the high-throughput analysis of such models,... read more 

Image registration is fundamental in medical imaging applications, such as disease progression analysis or radiation therapy planning. The primary objective of image registration is to precisely capture the deformation between two or more images, typ... read more 

Surgical video generation has drawn increasing attention due to its potential in surgical tasks. Existing methods usually emphasize the fitting of the original motion patterns. They are unable to reasonably extrapolate the learned motion patterns and... read more 

BACKGROUND: Colon cancer diagnosis from histopathology is challenging due to limited annotated data and the lack of interpretability in deep models. OBJECTIVE: We present a data-efficient framework combining few-shot learning and explainable AI for a... read more