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Performance Optimization of Fault Diagnosis Methods for Power Systems
This book focuses on the performance optimization of fault diagnosis methods for power systems including both model-driven ones, such as the linear...
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The present and future of minimally invasive methods for Alzheimer's disease diagnosis
Objective and methodsInvasive and noninvasive methods for diagnosing Alzheimer's disease (AD) are discussed and efforts to test less invasively are...
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Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project
BackgroundA major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five...
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Deep Federated Machine Learning-Based Optimization Methods for Liver Tumor Diagnosis: A Review
Computer-aided liver diagnosis helps doctors accurately identify liver abnormalities and reduce the risk of liver surgery. Early diagnosis and...
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Utility of clinicoradiological, microbiological, histopathological, and molecular methods in the diagnosis of spinal tuberculosis
PurposeThe diagnosis of STB is mainly based on clinicoradiological observations substantiated by bacterial culture, staining, Gene Xpert, and...
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Methods and Means for the Diagnosis and Monitoring of Diseases: Improvements in Methods and Approaches to Analysis
A brief overview of the main areas of research presented in the section “Methods and tools for diagnosing and treating diseases” at the XV...
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Diagnosis of Mycobacterium
This book covers all the aspects related to the laboratory diagnosis of Mycobacterium.Laboratory diagnosis includes microscopic to advance molecular...
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Current advances in noninvasive methods for the diagnosis of oral squamous cell carcinoma: a review
Oral squamous cell carcinoma (OSCC), one of the most common types of cancers worldwide, is diagnosed mainly through tissue biopsy. However, owing to...
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Detection and diagnosis of process fault using unsupervised learning methods and unlabeled data
Supervised learning methods, commonly used for process monitoring, require labeled historical datasets for normal condition as well for each faulty...
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Diagnosis
This chapter contains an overview of all the clinical trials on Alzheimer’s disease diagnosis based on ocular biomarkers. The chapter covers...
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Diagnosis
This chapterDiagnosis covers the clinical application of diagnosis of cardiovascular disease. A clinical opinion piece discusses the current clinical...
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Spectroscopic methods for COVID-19 detection and early diagnosis
The coronavirus pandemic is a worldwide hazard that poses a threat to millions of individuals throughout the world. This pandemic is caused by the...
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Fault Diagnosis Methods of Deep Convolutional Dynamic Adversarial Networks
A DCDAN is proposed for intelligent fault diagnosis to address the issue that it is easy to obtain a large amount of labeled fault-type data in a...
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Overview on Fault Detection and Diagnosis Methods in Building HVAC Systems: Toward a Hybrid Approach
This paper aims to provide a summarized classification of fault detection and diagnosis (FDD) methods in Heating Ventilation and Air Conditioning...
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Recent Advances in Melanoma Diagnosis and Prognosis Using Machine Learning Methods
Purpose of ReviewThe purpose was to summarize the current role and state of artificial intelligence and machine learning in the diagnosis and...
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A systematic analysis of magnetic resonance images and deep learning methods used for diagnosis of brain tumor
Accurate classification and segmentation of brain tumors is a critical task to perform. The term classification is the process of grading tumors...
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Model-Based Fault Diagnosis Methods for State-Space Systems
This book investigates in detail model-based fault diagnosis methods, including observer-based residual generation, residual evaluation based on...
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Improved intelligent methods for power transformer fault diagnosis based on tree ensemble learning and multiple feature vector analysis
This paper discusses the impact of the feature input vector on the performance of dissolved gas analysis-based intelligent power transformer fault...
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A mixed methods study to uncover impediments to accurate diagnosis of nonradiographic axial spondyloarthritis in the USA
Introduction/objectivesDelayed diagnosis of axial spondyloarthritis (axSpA) is well documented; little is known about the diagnostic journey and...
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A new computer-aided diagnosis tool based on deep learning methods for automatic detection of retinal disorders from OCT images
PurposeEarly detection of retinal disorders using optical coherence tomography (OCT) images can prevent vision loss. Since manual screening can be...
