Artificial Intelligence Medical Compendium

OBJECTIVES: To develop and do multicenter validation on an algorithm that screens for osteoporosis from abdominal CTs. METHODS: This is a diagnostic accuracy study with retrospective data from January 2022 to July 2022 consisting of two steps: a segm... read more 

OBJECTIVES: This study aims to develop an artificial intelligence (AI)-based automated segmentation method for small renal masses (SRMs) using multi-center, multi-scanner, multi-sequence MRI data. METHODS: MR images from 988 pathologically confirmed ... read more 

OBJECTIVES: Parametric tissue mapping enables quantitative cardiac tissue characterization but is limited by inter-observer variability during manual delineation. Traditional approaches relying on average relaxation values and single cutoffs may over... read more 

The abuse of stimulants poses a significant threat to public health and the integrity of competitive sports, necessitating the development of highly sensitive and rapid-response detection technologies for effective regulation. This study integrates S... read more 

HIV specifically targets the immune system's T cells, mainly the CD4+ T cells, leading to a chronic and severe illness characterized by a long incubation period. In this study, we propose a novel nonlinear fractional-order model for analyzing and con... read more 

BACKGROUND: Identifying the brand of reverse shoulder arthroplasty (rTSA) implanted is key in the postoperative evaluation of patients, a process that can be time-consuming and prone to error. This is particularly relevant when rTSA is considered for... read more 

This study investigated the associations between corn raw material/process parameters and chemical components after anaerobic fermentation using machine learning (ML). High-quality experimental data from 140 academic papers were utilized for model tr... read more 

BACKGROUND: Minimizing postoperative complications is imperative to improving patient outcomes. The purpose of this investigation is to develop machine learning (ML) models that can predict complications following open reduction and internal fixation... read more 

Algorithmic decision support is rapidly becoming a staple of personalized medicine, particularly for high-stakes recommendations such as cancer subtyping in which access to patient-specific information can drastically alter the course of treatment, a... read more 

In recent years, deep learning techniques have been increasingly adopted in soft sensor modeling, with the transformer architecture demonstrating notable advantages not only in natural language processing and image analysis but also in time-series mo... read more