Artificial Intelligence Medical Compendium

KEY POINTS: Proteomics analyses consistently identified nine independent protein predictors for CKD in both Chinese and European participants with type 2 diabetes. A novel prediction model, "eGFR+five-protein panel predicting CKD," reliably predicted... read more 

OBJECTIVE: To assess whether accelerated knee MRI protocols using simultaneous multi-slice (SMS) and deep learning reconstruction (DLR) are non-inferior to a conventional parallel imaging protocol for detecting internal derangement injuries. METHODS:... read more 

BACKGROUND: Basal cell carcinoma (BCC) is the most common skin cancer, requiring an early diagnosis and accurate margin definition to prevent functional and cosmetic complications. Traditional methods using clinical and dermoscopic images (C&D) often... read more 

PURPOSE: Early onset scoliosis comprises spinal deformities in children younger than 10, creating challenges in diagnosis, risk assessment, and management. Timely intervention is vital, because untreated deformity can lead to cardiopulmonary compromi... read more 

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OBJECTIVE: Aims to develop a standardized evaluation method based on the YOLOv8n object detection algorithm, with the goal of quantitatively assessing the displacement of orthokeratology lenses (OK_lenses) and objectively evaluating their fitting sta... read more 

This paper investigates the privacy-preserving protocol and reinforcement learning-based funnel controller design of multi-agent systems subject to input dead-zone constraints. An adaptive funnel controller is formulated to guarantee that the trackin... read more 

BACKGROUND: Neonatal diseases represent the leading cause of death in Nigeria, ranking the country second globally in neonatal mortality rates. Early and accurate diagnosis remains challenging, leading to delayed interventions and increased mortality... read more 

Diffusion Models (DMs) stand out among generative models for their impressive capabilities, but their application is often constrained by slower inference speeds and higher computational costs. Previous works have attempted to address these issues th... read more 

Mesh smoothing methods can enhance mesh quality by eliminating distorted elements, leading to improved convergence in simulations. To balance the efficiency and robustness of traditional mesh smoothing process, previous approaches have employed super... read more