AIMC Topic: Aged
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Non-invasive liver fibrosis screening on CT images using radiomics.
BMC medical imaging
Jul 15, 2025
PURPOSE: To develop a radiomics machine learning model for detecting liver fibrosis on CT images of the liver.
Ultrafast T2-weighted MR imaging of the urinary bladder using deep learning-accelerated HASTE at 3 Tesla.
BMC medical imaging
Jul 15, 2025
OBJECTIVE: This prospective study aimed to assess the feasibility of a half-Fourier single-shot turbo spin echo sequence (HASTE) with deep learning (DL) reconstruction for ultrafast imaging of the bladder with reduced susceptibility to motion artifac...
Objective monitoring of motor symptom severity and their progression in Parkinson's disease using a digital gait device.
Scientific reports
Jul 15, 2025
Digital technologies for monitoring motor symptoms of Parkinson's Disease (PD) underwent a strong evolution during the past years. Although it has been shown for several devices that derived digital gait features can reliably discriminate between hea...
Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer.
Scientific reports
Jul 15, 2025
Although neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the standard treatment for stage II and III esophageal cancers, it is associated with severe adverse events caused by docetaxel. Consequently, this study aime...
Preoperative prediction value of 2.5D deep learning model based on contrast-enhanced CT for lymphovascular invasion of gastric cancer.
Scientific reports
Jul 15, 2025
To develop and validate artificial intelligence models based on contrast-enhanced CT(CECT) images of venous phase using deep learning (DL) and Radiomics approaches to predict lymphovascular invasion in gastric cancer prior to surgery. We retrospectiv...
Evaluating cognitive decline detection in aging populations with single-channel EEG features based on two studies and meta-analysis.
Scientific reports
Jul 15, 2025
Timely detection of cognitive decline is paramount for effective intervention, prompting researchers to leverage EEG pattern analysis, focusing particularly on cognitive load, to establish reliable markers for early detection and intervention. This c...
Poincare guided geometric UNet for left atrial epicardial adipose tissue segmentation in Dixon MRI images.
Scientific reports
Jul 15, 2025
Epicardial Adipose Tissue (EAT) is a recognized risk factor for cardiovascular diseases and plays a pivotal role in the pathophysiology of Atrial Fibrillation (AF). Accurate automatic segmentation of the EAT around the Left Atrium (LA) from Magnetic ...
Multimodal Detection of Agitation in People With Dementia in Clinical Settings: Observational Pilot Study.
JMIR aging
Jul 15, 2025
BACKGROUND: Dementia is a progressive neurodegenerative condition that affects millions worldwide, often accompanied by agitation and aggression (AA), which contribute to patient distress and increased health care burden. Existing assessment methods ...
Predicting patient risk of leaving without being seen using machine learning: a retrospective study in a single overcrowded emergency department.
BMC emergency medicine
Jul 15, 2025
Emergency department (ED) overcrowding has become a critical issue in hospital management, leading to increased patient wait times and higher rates of individuals leaving without being seen (LWBS). This study aims to identify key factors influencing ...
Using machine learning algorithms to predict risk factors of heart failure after complete mesocolic excision in colorectal cancer patients.
Scientific reports
Jul 15, 2025
Following complete mesocolic excision (CME), heart failure (HF) emerges as a significant complication, exerting substantial impacts on both short-term and long-term patient prognoses. The primary objective of our investigation was to develop a machin...
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