AIMC Topic: Middle Aged

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Interpretable machine learning models for detecting peripheral neuropathy and lower extremity arterial disease in diabetics: an analysis of critical shared and unique risk factors.

BMC medical informatics and decision making Jul 22, 2024
BACKGROUND: Diabetic peripheral neuropathy (DPN) and lower extremity arterial disease (LEAD) are significant contributors to diabetic foot ulcers (DFUs), which severely affect patients' quality of life. This study aimed to develop machine learning (M...
Machine Learning Retrospective Studies Female Risk Factors Aged Male Middle Aged Lower Extremity Peripheral Arterial Disease Humans Diabetic Foot Diabetic Neuropathies
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Differentiation of granulomatous nodules with lobulation and spiculation signs from solid lung adenocarcinomas using a CT deep learning model.

BMC cancer Jul 22, 2024
BACKGROUND: The diagnosis of solitary pulmonary nodules has always been a difficult and important point in clinical research, especially granulomatous nodules (GNs) with lobulation and spiculation signs, which are easily misdiagnosed as malignant tum...
Middle Aged Deep Learning Lung Neoplasms Tomography, X-Ray Computed Solitary Pulmonary Nodule Diagnosis, Differential Humans Female Granuloma Retrospective Studies Aged Adenocarcinoma of Lung Adult Male
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Using machine learning-based algorithms to construct cardiovascular risk prediction models for Taiwanese adults based on traditional and novel risk factors.

BMC medical informatics and decision making Jul 22, 2024
OBJECTIVE: To develop and validate machine learning models for predicting coronary artery disease (CAD) within a Taiwanese cohort, with an emphasis on identifying significant predictors and comparing the performance of various models.
Lipids Taiwan Coronary Artery Disease Biological Specimen Banks Sex Factors Heart Disease Risk Factors Early Diagnosis Smoking Alcohol Drinking Adult Humans Male Machine Learning Middle Aged Biomarkers Risk Assessment Retrospective Studies Age Factors Female Aged
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Machine learning analysis of lab tests to predict bariatric readmissions.

Scientific reports Jul 22, 2024
The purpose of this study was to develop a machine learning model for predicting 30-day readmission after bariatric surgery based on laboratory tests. Data were collected from patients who underwent bariatric surgery between 2018 and 2023. Laboratory...
Male Middle Aged ROC Curve Support Vector Machine Bariatric Surgery Humans Machine Learning Female Adult Patient Readmission
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Endobronchial Ultrasound-Based Support Vector Machine Model for Differentiating between Benign and Malignant Mediastinal and Hilar Lymph Nodes.

Respiration; international review of thoracic diseases Jul 22, 2024
INTRODUCTION: The aim of the study was to establish an ultrasonographic radiomics machine learning model based on endobronchial ultrasound (EBUS) to assist in diagnosing benign and malignant mediastinal and hilar lymph nodes (LNs).
Lung Neoplasms Adult Lymph Nodes Male Humans Bronchoscopy Support Vector Machine Middle Aged Retrospective Studies Diagnosis, Differential ROC Curve Lymphatic Metastasis Female Endosonography Aged Mediastinum
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Predicting postoperative visual acuity in epiretinal membrane patients and visualization of the contribution of explanatory variables in a machine learning model.

PloS one Jul 22, 2024
BACKGROUND: The purpose of this study was to develop a model that can predict the postoperative visual acuity in eyes that had undergone vitrectomy for an epiretinal membrane (ERM). The Light Gradient Boosting Machine (LightGBM) was used to evaluate ...
Middle Aged Visual Acuity Tomography, Optical Coherence Postoperative Period Vitrectomy Machine Learning Epiretinal Membrane Female Humans Aged Male
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Constructing prediction models and analyzing factors in suicidal ideation using machine learning, focusing on the older population.

PloS one Jul 22, 2024
Suicide among the older population is a significant public health concern in South Korea. As the older individuals have long considered suicide before committing suicide trials, it is important to analyze the suicidal ideation that precedes the suici...
Suicidal Ideation Logistic Models Socioeconomic Factors Health Status Mental Health Male Middle Aged Suicide, Attempted Republic of Korea Humans Female Machine Learning Risk Factors Aged Aged, 80 and over Algorithms
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Utility of Thin-slice Fat-suppressed Single-shot T2-weighted MR Imaging with Deep Learning Image Reconstruction as a Protocol for Evaluating the Pancreas.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Jul 21, 2024
PURPOSE: To compare the utility of thin-slice fat-suppressed single-shot T2-weighted imaging (T2WI) with deep learning image reconstruction (DLIR) and conventional fast spin-echo T2WI with DLIR for evaluating pancreatic protocol.
Pancreatic Neoplasms Aged Humans Image Interpretation, Computer-Assisted Aged, 80 and over Male Middle Aged Deep Learning Pancreas Signal-To-Noise Ratio Gadolinium DTPA Retrospective Studies Female Image Processing, Computer-Assisted Contrast Media Magnetic Resonance Imaging Adipose Tissue
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Machine learning-based prediction of vancomycin concentration after abdominal administration in patients with peritoneal dialysis-related peritonitis.

Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy Jul 21, 2024
INTRODUCTION: Peritonitis is a serious complication of peritoneal dialysis (PD), in which insufficient control of antibacterial drug concentrations poses a significant risk for poor outcomes. Predicting antibacterial drug concentrations is crucial in...
Peritoneal Dialysis Anti-Bacterial Agents Retrospective Studies Female Aged Adult Male Humans Middle Aged Vancomycin Machine Learning Peritonitis
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ICURE: Intensive care unit (ICU) risk evaluation for 30-day mortality. Developing and evaluating a multivariable machine learning prediction model for patients admitted to the general ICU in Sweden.

Acta anaesthesiologica Scandinavica Jul 21, 2024
BACKGROUND: A prediction model that estimates mortality at admission to the intensive care unit (ICU) is of potential benefit to both patients and society. Logistic regression models like Simplified Acute Physiology Score 3 (SAPS 3) and APACHE are th...
Female Sweden Aged Aged, 80 and over Adult Humans Machine Learning Intensive Care Units Logistic Models Registries Simplified Acute Physiology Score Male Middle Aged Risk Assessment Hospital Mortality
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