AIMC Topic: Aged, 80 and over
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Image quality assessment of artificial intelligence iterative reconstruction for low dose unenhanced abdomen: comparison with hybrid iterative reconstruction.
Abdominal radiology (New York)
Dec 21, 2024
OBJECTIVES: To assess the impact of artificial intelligence iterative reconstruction algorithms (AIIR) on image quality with phantom and clinical studies.
Deep learning model for automated detection of fresh and old vertebral fractures on thoracolumbar CT.
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Dec 21, 2024
PURPOSE: To develop a deep learning system for automatic segmentation of compression fracture vertebral bodies on thoracolumbar CT and differentiate between fresh and old fractures.
Application of machine learning methods for predicting esophageal variceal bleeding in patients with cirrhosis.
European radiology
Dec 21, 2024
OBJECTIVE: To develop and compare machine learning models based on CT morphology features, serum biomarkers, and basic physical conditions to predict esophageal variceal bleeding.
Understanding Daily Care Experience Preferences Across the Lifespan of Older Adults: Application of Natural Language Processing.
Western journal of nursing research
Dec 21, 2024
INTRODUCTION: Older adults are a heterogeneous group, and their care experience preferences are likely to be diverse and individualized. Thus, the aim of this study was to identify categories of older adults' care experience preferences and to examin...
Longitudinal changes following the introduction of socially assistive robots in nursing homes: a qualitative study with ICF framework and causal loop diagramming.
BMC geriatrics
Dec 21, 2024
BACKGROUND: Socially assistive robots introduced in nursing care settings have multidimensional psychological impacts on care recipients and caregivers. This study aims to explore the longitudinal changes induced by socially assistive robots, focusin...
Using clinical data to reclassify ESUS patients to large artery atherosclerotic or cardioembolic stroke mechanisms.
Journal of neurology
Dec 21, 2024
PURPOSE: Embolic stroke of unidentified source (ESUS) represents 10-25% of all ischemic strokes. Our goal was to determine whether ESUS could be reclassified to cardioembolic (CE) or large-artery atherosclerosis (LAA) with machine learning (ML) using...
Improving the prediction of chemotherapy dose-limiting toxicity in colon cancer patients using an AI-CT-based 3D body composition of the entire L1-L5 lumbar spine.
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Dec 21, 2024
PURPOSE: Chemotherapy dose-limiting toxicities (DLT) pose a significant challenge in successful colon cancer treatment. Body composition analysis may enable tailored interventions thereby supporting the mitigation of chemotherapy toxic effects. This ...
Protocol for the impact of machine learning-based clinician decision support algorithims in perioperative care (IMAGINATIVE) in Singapore general hospital : a large prospective randomised controlled trial.
BMJ open
Dec 20, 2024
INTRODUCTION: As surgical accessibility improves, the incidence of postoperative complications is expected to rise. The implementation of a precise and objective risk stratification tool holds the potential to mitigate these complications by early id...
Aged, 80 and over
Elective Surgical Procedures
Humans
Young Adult
Singapore
Risk Assessment
Machine Learning
Adult
Hospitals, General
Postoperative Complications
Prospective Studies
Male
Perioperative Care
Decision Support Systems, Clinical
Intensive Care Units
Middle Aged
Randomized Controlled Trials as Topic
Female
Aged
Image quality assessment and white matter hyperintensity quantification in two accelerated high-resolution 3D FLAIR techniques: Wave-CAIPI and deep learning-based SPACE.
Clinical radiology
Dec 19, 2024
AIM: To compare the image quality obtained using two accelerated high-resolution 3D fluid-attenuated inversion recovery (FLAIR) techniques for the brain-deep learning-reconstruction SPACE (DL-SPACE) and Wave-CAIPI FLAIR.
Explainable machine learning on clinical features to predict and differentiate Alzheimer's progression by sex: Toward a clinician-tailored web interface.
Journal of the neurological sciences
Dec 19, 2024
Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasiv...
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