Artificial Intelligence Medical Compendium

OBJECTIVE: To develop and validate a radiomics-based machine learning nomogram using multiparametric MRI for preoperative prediction of aggressive histology in endometrial cancer (EC) patients. METHODS: This dual-center study retrospectively analyzed... read more 

OBJECTIVE: This systematic review critically appraises the current landscape of physics-aware artificial intelligence (AI) in medical imaging for quantitative biomarker mapping in Metabolic dysfunction-associated steatotic liver disease (MASLD) and i... read more 

Accurate assessment of jumping is important for sports performance and rehabilitation. While laboratory-based motion capture is considered gold-standard, markerless motion capture (MMC) systems offer an accessible alternative for field and clinical s... read more 

AIM: The aim of this integrative review is to critically appraise and synthesise empirical evidence on the clinical applications, outcomes, and implications of generative artificial intelligence in nursing practice. DESIGN: Integrative review followi... read more 

With the ever-expanding amount of data, students increasingly find themselves needing to engage in self-directed learning to be successful. Students studying science, technology, engineering, and mathematics often struggle with self-directed learning... read more 

OBJECTIVE: Fetal growth restriction (FGR) is a progressive condition that amplifies risks with advancing gestation. This study develops a time-dependent random survival forest (RSF) model integrating prenatal screening markers to predict FGR and expl... read more 

INTRODUCTION: In the Movement Disorder Society criteria for the diagnosis of Parkinson's disease (PD), evaluation of the presynaptic dopamine system should be performed using dopamine transporter single-photon emission computed tomography (DAT SPECT)... read more 

The recurrent and often unpredictable course of affective disorders poses a critical challenge for long-term patient care. The CRC/TRR 393 consortium has established an ambitious longitudinal study, the German Mental Health Cohort (GEMCO), to systema... read more 

PURPOSE: To implement and evaluate the feasibility of a Pilot Tone (PT)-based prospective gating and tracking technique, which uses a long short-term memory (LSTM) neural network to predict respiratory motion from PT signals. METHODS: A subject-speci... read more 

BACKGROUND: Although radiographs are the first-line imaging modality, differentiating between neoplastic pathologic fractures and nonpathologic fractures on radiographs can sometimes be challenging. In this study, we aimed to develop and evaluate a d... read more