Artificial Intelligence Medical Compendium

In this paper, we propose a novel diffusion model-based dynamic graph clustering method to address the challenge of evolving graph structures, where new nodes may belong to unknown classes. Existing deep graph clustering approaches exhibit strong per... read more 

Cancer frequently co-occurs with other chronic conditions, contributing substantially to disease burden. Multimorbidity is an increasing public health concern, resulting from complex interactions between sociodemographic, lifestyle, and environmental... read more 

BACKGROUND: Chronic pain around the temporomandibular joint (TMJ) and masticatory muscles is a primary symptom of temporomandibular disorders (TMD). However, the clinical significance of magnetic resonance imaging (MRI) features in predicting TMD-rel... read more 

STUDY OBJECTIVE: To compare the use of ambient artificial intelligence (AI) versus human scribes in the emergency department in terms of note quality and time spent in the electronic health record. METHODS: A quality improvement pilot was performed w... read more 

OBJECTIVES: The performance of fully automated deep learning-based models for the detection and segmentation of lymph nodes (LNs) on full- and simulated reduced-dose CT was validated. METHODS: A total of 15,341 LNs were annotated in 151 patient CTs (... read more 

PURPOSE: Pancreatic cystic lesions (PCL) commonly undergo surveillance using MRI with MR cholangiopancreatography (MRCP). Our objective is to compare the performance of a single-shot fat-saturated T2-weighted technique with deep-learning reconstructi... read more 

OBJECTIVES: This study aims to automate segmentation of the biliary and pancreatic systems on 3D negative-contrast CT cholangiopancreatography (3D-nCTCP) to improve preoperative planning and diagnosis. METHODS: We retrospectively collected dual-phase... read more 

OBJECTIVE: To develop and evaluate a comprehensive AI-driven pipeline for automated segmentation and multi-class classification of ovarian tumors in ultrasound images using advanced transformer-based models and radiomic analysis. MATERIALS AND METHOD... read more 

OBJECTIVES: Accurate prediction of response to first-line oxaliplatin-based chemotherapy in unresectable colorectal liver metastases (CRLM) is critical for optimizing treatment strategies. This study aimed to develop and validate a dual-phase CT-base... read more 

PURPOSE: High-sensitivity, total-body (TB) positron emission tomography (PET) and computed tomography (CT) imaging systems enable substantial reduction of injected radioactivity without compromising image quality. Synthetic CT-like attenuation maps c... read more