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Recommender-based bone tumour classification with radiographs—a link to the past
ObjectivesTo develop an algorithm to link undiagnosed patients to previous patient histories based on radiographs, and simultaneous classification of...
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Robust prostate disease classification using transformers with discrete representations
Purpose:Automated prostate disease classification on multi-parametric MRI has recently shown promising results with the use of convolutional neural...
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Tumor classification of gastrointestinal liver metastases using CT-based radiomics and deep learning
ObjectivesThe goal of this study is to demonstrate the performance of radiomics and CNN-based classifiers in determining the primary origin of...
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Automated classification of polyps using deep learning architectures and few-shot learning
BackgroundColorectal cancer is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. However, not all...
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Automated detection of fatal cerebral haemorrhage in postmortem CT data
During the last years, the detection of different causes of death based on postmortem imaging findings became more and more relevant. Especially...
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A systematic review of machine learning models for management, prediction and classification of ARDS
AimAcute respiratory distress syndrome or ARDS is an acute, severe form of respiratory failure characterised by poor oxygenation and bilateral...
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Preliminary study on the application of renal ultrasonography radiomics in the classification of glomerulopathy
BackgroundThe aim of this study was to investigate the potential use of renal ultrasonography radiomics features in the histologic classification of...
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Comparison of classification algorithms for predicting autistic spectrum disorder using WEKA modeler
BackgroundIn healthcare area, big data, if integrated with machine learning, enables health practitioners to predict the result of a disorder or...
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Classification of benign and malignant subtypes of breast cancer histopathology imaging using hybrid CNN-LSTM based transfer learning
BackgroundGrading of cancer histopathology slides requires more pathologists and expert clinicians as well as it is time consuming to look manually...
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Artificial Intelligence for Pre-operative Diagnosis of Malignant Thyroid Nodules Based on Sonographic Features and Cytology Category
BackgroundCurrent diagnosis and classification of thyroid nodules are susceptible to subjective factors. Despite widespread use of ultrasonography...
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Skeletal muscle and intermuscular adipose tissue gene expression profiling identifies new biomarkers with prognostic significance for insulin resistance progression and intervention response
Aims/hypothesisAlthough insulin resistance often leads to type 2 diabetes mellitus, its early stages are often unrecognised, thus reducing the...
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Horse Herd Optimization with Gate Recurrent Unit for an Automatic Classification of Different Facial Skin Disease
The human body’s largest organ is the skin which covers the entire body. The facial skin is one area of the body that needs careful handling. It can...
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Affinity scores: An individual-centric fingerprinting framework for neuropsychiatric disorders
Population-centric frameworks of biomarker identification for psychiatric disorders focus primarily on comparing averages between groups and assume...
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Genetic matching for time-dependent treatments: a longitudinal extension and simulation study
BackgroundLongitudinal matching can mitigate confounding in observational, real-world studies of time-dependent treatments. To date, these methods...
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Laparoscopic versus open parenchymal sparing liver resections for high tumour burden colorectal liver metastases: a propensity score matched analysis
BackgroundLaparoscopic liver resection (LLR) has proved effective in the treatment of oligometastatic disease (1 or 2 colorectal liver metastases...
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Exploiting mutual information for the imputation of static and dynamic mixed-type clinical data with an adaptive k-nearest neighbours approach
BackgroundClinical registers constitute an invaluable resource in the medical data-driven decision making context. Accurate machine learning and data...
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Type, density, and healthiness of food-outlets in a university foodscape: a geographical map** and characterisation of food resources in a Ghanaian university campus
IntroductionFood environments are viewed as the interface where individuals interact with the wider food system to procure and/or consume food....
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Comparative effectiveness of sodium-glucose cotransporter-2 inhibitors for new-onset gastric cancer and gastric diseases in patients with type 2 diabetes mellitus: a population-based cohort study
ObjectiveTo compare the risks of gastric cancer and other gastric diseases in patients with type-2 diabetes mellitus (T2DM) exposed to sodium-glucose...
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Interpretable prediction of 3-year all-cause mortality in patients with chronic heart failure based on machine learning
BackgroundThe goal of this study was to assess the effectiveness of machine learning models and create an interpretable machine learning model that...
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Development of machine learning models aiming at knee osteoarthritis diagnosing: an MRI radiomics analysis
BackgroundTo develop and assess the performance of machine learning (ML) models based on magnetic resonance imaging (MRI) radiomics analysis for knee...
