AIMC Topic: Aged
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Development of machine learning-based models for predicting risk factors in acute cerebral infarction patients: a clinical retrospective study.
BMC neurology
Aug 31, 2024
OBJECTIVES: The aim of this study was to develop machine learning-based models for predicting acute cerebral infarction (ACI) in patients.
Deep learning approach for dysphagia detection by syllable-based speech analysis with daily conversations.
Scientific reports
Aug 31, 2024
Dysphagia, a disorder affecting the ability to swallow, has a high prevalence among the older adults and can lead to serious health complications. Therefore, early detection of dysphagia is important. This study evaluated the effectiveness of a newly...
Machine learning techniques to identify risk factors of breast cancer among women in Mashhad, Iran.
Journal of preventive medicine and hygiene
Aug 31, 2024
BACKGROUND: Low survival rates of breast cancer in developing countries are mainly due to the lack of early detection plans and adequate diagnosis and treatment facilities.
Development and validation of a prediction model for malignant sinonasal tumors based on MR radiomics and machine learning.
European radiology
Aug 30, 2024
OBJECTIVES: This study aimed to utilize MR radiomics-based machine learning classifiers on a large-sample, multicenter dataset to develop an optimal model for predicting malignant sinonasal tumors and tumor-like lesions.
Development and External Validation of a Motor Intention-Integrated Prediction Model for Upper Extremity Motor Recovery After Intention-Driven Robotic Hand Training for Chronic Stroke.
Archives of physical medicine and rehabilitation
Aug 30, 2024
OBJECTIVE: To derive and validate a prediction model for minimal clinically important differences (MCIDs) in upper extremity (UE) motor function after intention-driven robotic hand training using residual voluntary electromyography (EMG) signals from...
Deep learning for efficient reconstruction of highly accelerated 3D FLAIR MRI in neurological deficits.
Magma (New York, N.Y.)
Aug 30, 2024
OBJECTIVE: To compare compressed sensing (CS) and the Cascades of Independently Recurrent Inference Machines (CIRIM) with respect to image quality and reconstruction times when 12-fold accelerated scans of patients with neurological deficits are reco...
Humans
Algorithms
Signal-To-Noise Ratio
Nervous System Diseases
White Matter
Deep Learning
Young Adult
Adolescent
Brain
Adult
Child, Preschool
Female
Male
Child
Magnetic Resonance Imaging
Reproducibility of Results
Middle Aged
Image Interpretation, Computer-Assisted
Aged
Imaging, Three-Dimensional
Artifacts
Image Processing, Computer-Assisted
An Integrated Radiopathomics Machine Learning Model to Predict Pathological Response to Preoperative Chemotherapy in Gastric Cancer.
Academic radiology
Aug 30, 2024
RATIONALE AND OBJECTIVES: Accurately predicting the pathological response to chemotherapy before treatment is important for selecting the appropriate treatment groups, formulating individualized treatment plans, and improving the survival rates of pa...
Construction and verification of a machine learning-based prediction model of deep vein thrombosis formation after spinal surgery.
International journal of medical informatics
Aug 30, 2024
BACKGROUND: Deep vein thromboembolism (DVT) is a common postoperative complication with high morbidity and mortality rates. However, the safety and effectiveness of using prophylactic anticoagulants for preventing DVT after spinal surgery remain cont...
Refining heart disease prediction accuracy using hybrid machine learning techniques with novel metaheuristic algorithms.
International journal of cardiology
Aug 30, 2024
Early diagnosis of heart disease is crucial, as it's one of the leading causes of death globally. Machine learning algorithms can be a powerful tool in achieving this goal. Therefore, this article aims to increase the accuracy of predicting heart dis...
Automated echocardiographic diastolic function grading: A hybrid multi-task deep learning and machine learning approach.
International journal of cardiology
Aug 30, 2024
BACKGROUND: Assessing left ventricular diastolic function (LVDF) with echocardiography as per ASE guidelines is tedious and time-consuming. The study aims to develop a fully automatic approach of this procedure by a lightweight hybrid algorithm combi...
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