Artificial Intelligence Medical Compendium

OBJECTIVE: Previous research suggests that adolescents with BPD (aBPD) exhibit distinct neuroanatomical alterations, although methodological limitations such as low sample size, and the reliance on univariate massive statistical analyses, prevent con... read more 

PURPOSE: The progression of acute kidney injury (AKI) to end-stage kidney disease (ESKD) poses challenges due to high risks of comorbidities and poor outcomes. This study aimed to develop and validate machine learning survival models for predicting E... read more 

BACKGROUND: Brain segmentation using structural MRI is effective for identifying regional atrophy in Parkinsonian syndromes. However, clinical validation of the automated deep learning-based brainstem segmentation model has been limited. PURPOSE: To ... read more 

BACKGROUND: Asthma is the most common chronic disease in children. Suboptimal asthma control is prevalent and causes significant health care costs. Electronic health records (EHRs) contain vast data which pose a major challenge for timely and efficie... read more 

INTRODUCTION: The use of Artificial Intelligence (AI) has grown dramatically in recent years. In addition to its use for data analysis, its applications have extended to manuscript writing. In this article, we analyze the policies within top neurosur... read more 

Antibiotic discovery and antibiotic prescribing represent two domains that both stand to benefit from artificial intelligence (AI)-driven progress in the near future. In this article, we discuss these parallel advances and the potential future synerg... read more 

PURPOSE OF REVIEW: The purpose of this study is to describe why this review is timely and relevant. Endotyping, the organization of rhinologic inflammation around immunologic precepts, has evolved from a research subject to a clinically relevant tool... read more 

Glioblastoma (GBM) continues to be the most lethal form of primary brain tumor. Therapeutic efficacy is significantly hindered by the presence of the blood-brain barrier (BBB) and the complex tumor microenvironment (TME), both of which contribute to ... read more 

OBJECTIVES: The purpose of this study was to create an operationally useful machine learning model that predicts the number of high-acuity left without being seen (LWBS) patients from the pediatric emergency department (ED). METHODS: We analyzed data... read more 

INTRODUCTION: Autism Spectrum Disorder (ASD) is characterized by deficits in social interaction and communication, including joint attention (JA) impairment. This observational case-control study explores quantitative JA metrics in ASD preschool-aged... read more