Πλοήγηση ανά Θέμα "Machine Learning"
Αποτελέσματα 1-17 από 17
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Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis
(2018)Over the years, MR systems have evolved from imaging modalities to advanced computational systems producing a variety of numerical parameters that can be used for the noninvasive preoperative assessment of breast pathology. ... -
Bone metastasis classification using whole body images from prostate cancer patients based on convolutional neural networks application
(2020)Bone metastasis is one of the most frequent diseases in prostate cancer; scintigraphy imaging is particularly important for the clinical diagnosis of bone metastasis. Up to date, minimal research has been conducted regarding ... -
Comparison of targeted and untargeted approaches in breath analysis for the discrimination of lung cancer from benign pulmonary diseases and healthy persons
(2021)The aim of the present study was to compare the efficiency of targeted and untargeted breath analysis in the discrimination of lung cancer (Ca+) patients from healthy people (HC) and patients with benign pulmonary diseases ... -
Data-driven machine-learning analysis of potential embolic sources in embolic stroke of undetermined source
(2021)Background and purpose: Hierarchical clustering, a common ‘unsupervised’ machine-learning algorithm, is advantageous for exploring potential underlying aetiology in particularly heterogeneous diseases. We investigated ... -
Efficient and targeted COVID-19 border testing via reinforcement learning
(2021)Throughout the coronavirus disease 2019 (COVID-19) pandemic, countries have relied on a variety of ad hoc border control protocols to allow for non-essential travel while safeguarding public health, from quarantining all ... -
Explainable machine learning for knee osteoarthritis diagnosis based on a novel fuzzy feature selection methodology
(2022)Knee Osteoarthritis (ΚΟΑ) is a degenerative joint disease of the knee that results from the progressive loss of cartilage. Due to KOA’s multifactorial nature and the poor understanding of its pathophysiology, there is a ... -
An explainable machine learning model for material backorder prediction in inventory management
(2021)Global competition among businesses imposes a more effective and low-cost supply chain allowing firms to provide products at a desired quality, quantity, and time, with lower production costs. The latter include holding ... -
Identification of most important features based on a fuzzy ensemble technique: Evaluation on joint space narrowing progression in knee osteoarthritis patients
(2021)Objective: Feature selection (FS) is a crucial and at the same time challenging processing step that aims to reduce the dimensionality of complex classification or regression problems. Various techniques have been proposed ... -
Interplay between oxidative damage, the redox status, and metabolic biomarkers during long-term fasting
(2020)Obesity and its related metabolic disorders, as well as infectious diseases like covid-19, are important health risks nowadays. It was recently documented that long-term fasting improves metabolic health and enhanced the ... -
Leveraging explainable machine learning to identify gait biomechanical parameters associated with anterior cruciate ligament injury
(2022)Anterior cruciate ligament (ACL) deficient and reconstructed knees display altered biomechanics during gait. Identifying significant gait changes is important for understanding normal and ACL function and is typically ... -
Machine learning and features for the prediction of thermal sensation and comfort using data from field surveys in Cyprus
(2022)Perception can influence individuals’ behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. ... -
Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status
(2020)Background: Combining MRI techniques with machine learning methodology is rapidly gaining attention as a promising method for staging of brain gliomas. This study assesses the diagnostic value of such a framework applied ... -
Machine learning for rhabdomyosarcoma histopathology
(2022)Correctly diagnosing a rare childhood cancer such as sarcoma can be critical to assigning the correct treatment regimen. With a finite number of pathologists worldwide specializing in pediatric/young adult sarcoma ... -
Machine Learning in Meningioma MRI: Past to Present. A Narrative Review
(2022)Meningioma is one of the most frequent primary central nervous system tumors. While magnetic resonance imaging (MRI), is the standard radiologic technique for provisional diagnosis and surveillance of meningioma, it ... -
Machine-Learning-Derived Model for the Stratification of Cardiovascular risk in Patients with Ischemic Stroke
(2021)Background Stratification of cardiovascular risk in patients with ischemic stroke is important as it may inform management strategies. We aimed to develop a machine-learning-derived prognostic model for the prediction of ... -
Patterns of 1,748 Unique Human Alloimmune Responses Seen by Simple Machine Learning Algorithms
(2020)Allele specific antibody response against the polymorphic system of HLA is the allogeneic response marker determining the immunological risk for graft acceptance before and after organ transplantation and therefore routinely ... -
Uncertainty-aware visual perception system for outdoor navigation of the visually challenged
(2020)Every day, visually challenged people (VCP) face mobility restrictions and accessibility limitations. A short walk to a nearby destination, which for other individuals is taken for granted, becomes a challenge. To tackle ...