AIMC Topic: Middle Aged

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Deep learning for quality assessment of axial T2-weighted prostate MRI: a tool to reduce unnecessary rescanning.

European radiology experimental
BACKGROUND: T2-weighted images are a critical component of prostate magnetic resonance imaging (MRI), and it would be useful to automatically assess image quality (IQ) on a patient-specific basis without radiologist oversight.

Predicting Visual Acuity after Retinal Vein Occlusion Anti-VEGF Treatment: Development and Validation of an Interpretable Machine Learning Model.

Journal of medical systems
Accurate prediction of post-treatment visual acuity in macular edema secondary to retinal vein occlusion (RVO-ME) is critical for optimizing anti-VEGF therapy and improving clinical outcomes. While machine learning (ML) has shown promise in ophthalmi...

From pixels to prognosis: leveraging radiomics and machine learning to predict IDH1 genotype in gliomas.

Neurosurgical review
Gliomas are the most common primary tumors of the central nervous system, and advances in genetics and molecular medicine have significantly transformed their classification and treatment. This study aims to predict the IDH1 genotype in gliomas using...

Urban walkability through different lenses: A comparative study of GPT-4o and human perceptions.

PloS one
Urban environments significantly shape our well-being, behavior, and overall quality of life. Assessing urban environments, particularly walkability, has traditionally relied on computer vision and machine learning algorithms. However, these approach...

Flexor Synergy Assessment and Therapy for Persons With Stroke Using the ULIX Low Impedance Robot.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The flexor synergy after stroke results in involuntary activation of distal muscles when lifting the shoulder against gravity. This contributes to impaired ability to perform activities of daily living. Robotic exoskeletons can be useful in assessing...

"I don't know": An uncertainty-aware machine learning model for predicting patient disposition at emergency department triage.

International journal of medical informatics
BACKGROUND: Machine learning (ML) models are widely used for predicting patient disposition at emergency department (ED) triage. However, these models generate predictions regardless of the level of uncertainty, potentially leading to overconfident o...

Risk calculator for long-term survival prediction of spinal chordoma versus chondrosarcoma: a nationwide analysis.

Journal of neuro-oncology
PURPOSE: Chordomas and chondrosarcomas are rare, aggressive spinal bone tumors with distinct origins, biological behavior, and treatment challenges, primarily due to their resistance to conventional chemotherapy and radiation. This study aimed to com...

Predicting Recurrence After Surgical Resection for High-Risk Localized Renal Cell Carcinoma: A Radiomics Clinical Integration Approach.

The Journal of urology
PURPOSE: Adjuvant immunotherapy for clear cell renal cell carcinoma (ccRCC) is controversial because of the absence of reliable biomarkers for identifying patients most likely to benefit. The aim of this study was to develop and validate a quantitati...

Machine learning models for minimizing aggravation in work-related musculoskeletal disorders among slaughterhouse workers.

Work (Reading, Mass.)
BackgroundWork-related musculoskeletal disorders (WMSDs) are common in Brazilian slaughterhouses. The repetitive and strenuous nature of meat processing, especially in slaughterhouses, makes employees highly susceptible to developing WMSDs. Prolonged...