AIMC Topic: Aged

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Development and Validation of Prediction Models for Incident Reversible Cognitive Frailty Based on Social-Ecological Predictors Using Generalized Linear Mixed Model and Machine Learning Algorithms: A Prospective Cohort Study.

Journal of applied gerontology : the official journal of the Southern Gerontological Society Aug 6, 2024
This study aimed to develop and validate prediction models for incident reversible cognitive frailty (RCF) based on social-ecological predictors. Older adults aged ≥60 years from China Health and Retirement Longitudinal Study (CHARLS) 2011-2013 surve...
Algorithms Prospective Studies Female Risk Factors Aged Humans Machine Learning Cognitive Dysfunction Longitudinal Studies Frailty Frail Elderly Linear Models Aged, 80 and over Male Middle Aged Risk Assessment China
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Deep learning approaches for the detection of scar presence from cine cardiac magnetic resonance adding derived parametric images.

Medical & biological engineering & computing Aug 6, 2024
This work proposes a convolutional neural network (CNN) that utilizes different combinations of parametric images computed from cine cardiac magnetic resonance (CMR) images, to classify each slice for possible myocardial scar tissue presence. The CNN...
Image Interpretation, Computer-Assisted Magnetic Resonance Imaging, Cine Male Middle Aged Deep Learning ROC Curve Cicatrix Humans Neural Networks, Computer Female Aged
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Artificial intelligence prediction of In-Hospital mortality in patients with dementia: A multi-center study.

International journal of medical informatics Aug 6, 2024
BACKGROUND: Prediction of mortality is very important for care planning in hospitalized patients with dementia and artificial intelligence has the potential to serve as a solution; however, this issue remains unclear. Thus, this study was conducted t...
Support Vector Machine Middle Aged Dementia Hospital Mortality Logistic Models Female Hospitalization Aged Aged, 80 and over Male Humans Artificial Intelligence Algorithms Electronic Health Records
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Ensemble machine learning to predict futile recanalization after mechanical thrombectomy based on non-contrast CT imaging.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Aug 6, 2024
OBJECTIVES: Despite successful recanalization after Mechanical Thrombectomy (MT), approximately 25 % of patients with Acute Ischemic Stroke (AIS) due to Large Vessel Occlusion (LVO) show unfavorable clinical outcomes, namely Futile Recanalization (FR...
Thrombectomy Medical Futility Aged, 80 and over Male Middle Aged Risk Assessment Time Factors Treatment Outcome Predictive Value of Tests Ischemic Stroke Radiographic Image Interpretation, Computer-Assisted Infarction, Middle Cerebral Artery Tomography, X-Ray Computed Clinical Decision-Making Female Risk Factors Aged Humans Machine Learning Decision Support Techniques Retrospective Studies
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Derivation and external validation of mass spectrometry-based proteomic model using machine learning algorithms to predict plaque rupture in patients with acute coronary syndrome.

Clinica chimica acta; international journal of clinical chemistry Aug 6, 2024
BACKGROUND: A poor prognosis is associated with atherosclerotic plaque rupture (PR) despite after conventional therapy for patients with acute coronary syndrome (ACS). Timely identification of PR improves the risk stratification and prognosis of ACS ...
Female Aged Male Middle Aged Cohort Studies Proteomics Mass Spectrometry Acute Coronary Syndrome Plaque, Atherosclerotic Humans Machine Learning Algorithms Biomarkers
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Combined High-Throughput Proteomics and Random Forest Machine-Learning Approach Differentiates and Classifies Metabolic, Immune, Signaling and ECM Intra-Tumor Heterogeneity of Colorectal Cancer.

Cells Aug 6, 2024
Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and tumor microenvironment (TME) variability. Intra-tumor heterogeneity and its connections with metabolic reprogramming an...
Proteomics Signal Transduction Epithelial-Mesenchymal Transition Humans Random Forest Machine Learning Extracellular Matrix Female Aged Colorectal Neoplasms Tumor Microenvironment Male Middle Aged
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Sex and population differences in the cardiometabolic continuum: a machine learning study using the UK Biobank and ELSA-Brasil cohorts.

BMC public health Aug 6, 2024
BACKGROUND: The temporal relationships across cardiometabolic diseases (CMDs) were recently conceptualized as the cardiometabolic continuum (CMC), sequence of cardiovascular events that stem from gene-environmental interactions, unhealthy lifestyle i...
Middle Aged Brazil Cohort Studies Longitudinal Studies Sex Factors United Kingdom Cardiometabolic Risk Factors UK Biobank Humans Machine Learning Female Aged Adult Male Cardiovascular Diseases
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A Deep Learning-Based Framework for Predicting Intracerebral Hematoma Expansion Using Head Non-contrast CT Scan.

Academic radiology Aug 5, 2024
RATIONALE AND OBJECTIVES: Hematoma expansion (HE) in intracerebral hemorrhage (ICH) is a critical factor affecting patient outcomes, yet effective clinical tools for predicting HE are currently lacking. We aim to develop a fully automated framework b...
Aged Sensitivity and Specificity Male Middle Aged Deep Learning Prospective Studies Retrospective Studies Tomography, X-Ray Computed Female Cerebral Hemorrhage Hematoma Humans
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Preoperative Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer Through Multimodal Deep Learning Based on Ultrasound and Magnetic Resonance Imaging Images.

Academic radiology Aug 5, 2024
RATIONALE AND OBJECTIVES: Deep learning can enhance the performance of multimodal image analysis, which is known for its noninvasive attributes and complementary efficacy, in predicting axillary lymph node (ALN) metastasis. Therefore, we established ...
Female Aged Adult Breast Neoplasms Middle Aged Humans Retrospective Studies Magnetic Resonance Imaging Axilla Multimodal Imaging Predictive Value of Tests Ultrasonography, Mammary Deep Learning Ultrasonography Lymph Nodes Lymphatic Metastasis
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Automated detection and classification of mandibular fractures on multislice spiral computed tomography using modified convolutional neural networks.

Oral surgery, oral medicine, oral pathology and oral radiology Aug 5, 2024
OBJECTIVE: To evaluate the performance of convolutional neural networks (CNNs) for the automated detection and classification of mandibular fractures on multislice spiral computed tomography (MSCT).
Adolescent Aged Radiographic Image Interpretation, Computer-Assisted Adult Humans Sensitivity and Specificity Neural Networks, Computer Multidetector Computed Tomography Male Retrospective Studies Tomography, Spiral Computed Middle Aged Female Mandibular Fractures
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