AIMC Topic: Aged
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A deep-learning algorithm using real-time collected intraoperative vital sign signals for predicting acute kidney injury after major non-cardiac surgeries: A modelling study.
PLoS medicine
Apr 29, 2025
BACKGROUND: Postoperative acute kidney injury (PO-AKI) prediction models for non-cardiac major surgeries typically rely solely on preoperative clinical characteristics.
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
Apr 29, 2025
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
Apr 28, 2025
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
Apr 28, 2025
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
Apr 28, 2025
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...
Detection of pathologic complete response using deep neural network-based endoscopic evaluation in patients with esophageal cancer receiving neoadjuvant chemotherapy: a nationwide multicenter retrospective study from 46 Japanese esophageal centers.
Esophagus : official journal of the Japan Esophageal Society
Apr 28, 2025
BACKGROUND: Detecting pathological complete response (pCR) preoperatively facilitated a non-surgical approach after neoadjuvant chemotherapy (NAC). We previously developed a deep neural network-based endoscopic evaluation to determine pCR preoperativ...
Neoadjuvant Therapy
Predictive Value of Tests
Esophageal Neoplasms
Japan
Esophageal Squamous Cell Carcinoma
Male
Middle Aged
Deep Learning
Treatment Outcome
Chemotherapy, Adjuvant
Esophagoscopy
Pathologic Complete Response
Humans
Neural Networks, Computer
Retrospective Studies
Female
Aged
Sensitivity and Specificity
Risk for ocular hypertension progression to early glaucoma: A predictive model and key predictors.
Photodiagnosis and photodynamic therapy
Apr 28, 2025
BACKGROUND: Ocular hypertension (OHT) is the most significant risk factor for glaucoma. We aimed to develop a model for predicting OHT progression to early glaucoma and to identify key predictors.
Predictive models of severe disease in patients with COVID-19 pneumonia at an early stage on CT images using topological properties.
Radiological physics and technology
Apr 28, 2025
Prediction of severe disease (SVD) in patients with coronavirus disease (COVID-19) pneumonia at an early stage could allow for more appropriate triage and improve patient prognosis. Moreover, the visualization of the topological properties of COVID-1...
Machine Learning-Based Radiomics in Malignancy Prediction of Pancreatic Cystic Lesions: Evidence from Cyst Fluid Multi-Omics.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Apr 28, 2025
The malignant potential of pancreatic cystic lesions (PCLs) varies dramatically, leading to difficulties when making clinical decisions. This study aimed to develop noninvasive clinical-radiomic models using preoperative CT images to predict the mali...
Gadoxetic acid-enhanced MRI for identifying cholangiocyte phenotype hepatocellular carcinoma by interpretable machine learning: individual application of SHAP.
BMC cancer
Apr 28, 2025
PURPOSE: Cholangiocyte phenotype hepatocellular carcinoma (HCC) is highly invasive. This study aims to develop and validate an optimal machine learning model to predict cholangiocyte phenotype HCC based on T1 mapping gadoxetic acid-enhanced MRI and t...
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