AIMC Topic: Aged
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Diagnosis of Sacroiliitis Through Semi-Supervised Segmentation and Radiomics Feature Analysis of MRI Images.
Journal of magnetic resonance imaging : JMRI
Feb 6, 2025
BACKGROUND: Sacroiliitis is a hallmark of ankylosing spondylitis (AS), and early detection plays an important role in managing the condition effectively. MRI is commonly used for diagnosing sacroiliitis, traditional methods often depend on subjective...
Young Adult
Adult
Sensitivity and Specificity
Radiomics
Male
Retrospective Studies
Female
Reproducibility of Results
Aged
Humans
Magnetic Resonance Imaging
Algorithms
Image Interpretation, Computer-Assisted
Middle Aged
Edema
Adolescent
Sacroiliac Joint
Child
Sacroiliitis
ROC Curve
Image Processing, Computer-Assisted
A Workflow-Efficient Approach to Pre- and Post-Operative Assessment of Weight-Bearing Three-Dimensional Knee Kinematics.
The Journal of arthroplasty
Feb 6, 2025
BACKGROUND: Knee kinematics during daily activities reflect disease severity preoperatively and are associated with clinical outcomes after total knee arthroplasty (TKA). It is widely believed that measured kinematics would be useful for preoperative...
Optimizing MR-based attenuation correction in hybrid PET/MR using deep learning: validation with a flatbed insert and consistent patient positioning.
European journal of nuclear medicine and molecular imaging
Feb 6, 2025
PURPOSE: To address the challenges of verifying MR-based attenuation correction (MRAC) in PET/MR due to CT positional mismatches and alignment issues, this study utilized a flatbed insert and arms-down positioning during PET/CT scans to achieve preci...
Predicting cognitive decline: Deep-learning reveals subtle brain changes in pre-MCI stage.
The journal of prevention of Alzheimer's disease
Feb 6, 2025
BACKGROUND: Mild cognitive impairment (MCI) and preclinical MCI (e.g., subjective cognitive decline, SCD) are considered risk states of dementia, such as Alzheimer's Disease (AD). However, it is challenging to accurately predict conversion from norma...
Aligning large language models with radiologists by reinforcement learning from AI feedback for chest CT reports.
European journal of radiology
Feb 6, 2025
BACKGROUND: Large language models (LLMs) often struggle to fully capture the nuanced preferences and clinical judgement of radiologists in medical report summarization even when fine-tuned on massive medical reports. This could lead to the generated ...
Machine learning-based plasma metabolomics for improved cirrhosis risk stratification.
BMC gastroenterology
Feb 6, 2025
BACKGROUND: Cirrhosis is a leading cause of mortality in patients with chronic liver disease (CLD). The rapid development of metabolomic technologies has enabled the capture of metabolic changes related to the progression of cirrhosis.
Integrating manual annotation with deep transfer learning and radiomics for vertebral fracture analysis.
BMC medical imaging
Feb 6, 2025
BACKGROUND: Vertebral compression fractures (VCFs) are prevalent in the elderly, often caused by osteoporosis or trauma. Differentiating acute from chronic VCFs is vital for treatment planning, but MRI, the gold standard, is inaccessible for some. Ho...
Cross-sectional design and protocol for Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI).
BMJ open
Feb 6, 2025
INTRODUCTION: Artificial Intelligence Ready and Equitable for Diabetes Insights (AI-READI) is a data collection project on type 2 diabetes mellitus (T2DM) to facilitate the widespread use of artificial intelligence and machine learning (AI/ML) approa...
Enhancing deep learning methods for brain metastasis detection through cross-technique annotations on SPACE MRI.
European radiology experimental
Feb 6, 2025
BACKGROUND: Gadolinium-enhanced "sampling perfection with application-optimized contrasts using different flip angle evolution" (SPACE) sequence allows better visualization of brain metastases (BMs) compared to "magnetization-prepared rapid acquisiti...
A comparison of different machine learning classifiers in predicting xerostomia and sticky saliva due to head and neck radiotherapy using a multi-objective, multimodal radiomics model.
Biomedical physics & engineering express
Feb 6, 2025
. Although radiotherapy techniques are a primary treatment for head and neck cancer (HNC), they are still associated with substantial toxicity and side effects. Machine learning (ML) based radiomics models for predicting toxicity mostly rely on featu...
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