AIMC Topic: Retrospective Studies

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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...
Diabetic Foot Humans Diabetic Neuropathies Aged Male Middle Aged Lower Extremity Peripheral Arterial Disease Machine Learning Retrospective Studies Female Risk Factors
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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...
Male Middle Aged Deep Learning Lung Neoplasms Granuloma Adenocarcinoma of Lung Solitary Pulmonary Nodule Diagnosis, Differential Tomography, X-Ray Computed Humans Female Aged Retrospective Studies Adult
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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.
Alcohol Drinking Humans Aged Heart Disease Risk Factors Age Factors Machine Learning Adult Early Diagnosis Lipids Biomarkers Male Biological Specimen Banks Smoking Retrospective Studies Taiwan Middle Aged Sex Factors Coronary Artery Disease Female Risk Assessment
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Development of machine learning models predicting mortality using routinely collected observational health data from 0-59 months old children admitted to an intensive care unit in Bangladesh: critical role of biochemistry and haematology data.

BMJ paediatrics open Jul 22, 2024
INTRODUCTION: Treatment in the intensive care unit (ICU) generates complex data where machine learning (ML) modelling could be beneficial. Using routine hospital data, we evaluated the ability of multiple ML models to predict inpatient mortality in a...
Infant Child, Preschool Hospital Mortality ROC Curve Bangladesh Intensive Care Units Female Infant, Newborn Male Humans Machine Learning Retrospective Studies
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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 Lymph Nodes Support Vector Machine Adult Humans Lymphatic Metastasis Bronchoscopy Endosonography Male Retrospective Studies Diagnosis, Differential Middle Aged Female Mediastinum ROC Curve Aged
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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.
Aged Aged, 80 and over Male Middle Aged Deep Learning Humans Retrospective Studies Female Pancreatic Neoplasms Image Interpretation, Computer-Assisted Pancreas Signal-To-Noise Ratio Image Processing, Computer-Assisted Gadolinium DTPA 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...
Middle Aged Vancomycin Peritonitis Peritoneal Dialysis Female Aged Adult Male Machine Learning Anti-Bacterial Agents Retrospective Studies Humans
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Application of a machine learning and optimization method to predict patellofemoral instability risk factors in children and adolescents.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Jul 21, 2024
PURPOSE: Conservative treatment remains the standard approach for first-time patellar dislocations. While risk factors for patellofemoral instability, a common paediatric injury, are well-established in adults, data concerning the progression of paed...
Patellar Dislocation Retrospective Studies Humans Adolescent Female Magnetic Resonance Imaging Child Machine Learning Risk Factors Patellofemoral Joint Male Joint Instability
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A deep learning approach to detection of oral cancer lesions from intra oral patient images: A preliminary retrospective study.

Journal of stomatology, oral and maxillofacial surgery Jul 21, 2024
INTRODUCTION: Oral squamous cell carcinomas (OSCC) seen in the oral cavity are a category of diseases for which dentists may diagnose and even cure. This study evaluated the performance of diagnostic computer software developed to detect oral cancer ...
Male Deep Learning Mouth Neoplasms Retrospective Studies Female Carcinoma, Squamous Cell Sensitivity and Specificity Humans
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Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity.

Acta radiologica (Stockholm, Sweden : 1987) Jul 21, 2024
BACKGROUND: The best settings of deep learning image reconstruction (DLIR) algorithm for abdominal low-kiloelectron volt (keV) virtual monoenergetic imaging (VMI) have not been determined.
Humans Aged Aged, 80 and over Adult Male Middle Aged Algorithms Retrospective Studies Tomography, X-Ray Computed Female Radiography, Abdominal Radiography, Dual-Energy Scanned Projection Deep Learning Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Signal-To-Noise Ratio
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