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Machine Learning In Data Analysis For Stroke Endovascular Therapy
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Book Synopsis Machine learning in data analysis for stroke/endovascular therapy by : Benjamin Yim
Download or read book Machine learning in data analysis for stroke/endovascular therapy written by Benjamin Yim and published by Frontiers Media SA. This book was released on 2023-09-05 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: With an estimated global incidence of 11 million patients per year, research involving ischemic stroke requires the collection and analysis of massive data sets affected by innumerable variables. Landmark studies that have historically shaped the foundation of our understanding of ischemic stroke and the development of management protocols have been derived from only a miniscule fraction of a percent of the entire population due to feasibility and capability. Machine learning provides an opportunity to capture data from an extraordinarily larger cohort size, which can be applied to training models to formulate algorithms to forecast outcomes with unparalleled accuracy and efficiency. The paradigm-shifting integration of machine learning in other industries, i.e. robotics, finance, and marketing, foreshadows its inevitable application to large population-based clinical research and practice. While prior multi-center studies have relied heavily on catalogued datasets requiring substantial manpower, the recent development of modern statistical methods can potentially expand the available quantity and quality of clinical data. In conjunction with data mining, machine learning has allowed automated extraction of clinical information from imaging, surgical videos, and electronic medical records to identify previously unseen patterns and create prediction models. Recently, it’s use in real-time detection of large vessel occlusion has streamlined health care delivery to a level of efficiency previously unmatched. The application of machine learning in ischemic stroke research – data acquisition, image evaluation, and prediction models – has the potential to reduce human error and increase reproducibility, accuracy, and precision with an unprecedented degree of power. However, one of the challenges with this integration remains the methods in which machine learning is utilized. Given the novelty of machine learning in clinical research, there remains significant variations in the application of machine learning tools and algorithms. The focus of the research topic is to provide a platform to compare the merits of various learning approaches – supervised, semi-supervised, unsupervised, self-learning – and the performances of various models.
Book Synopsis Big data analytics to advance stroke and cerebrovascular disease: A tool to bridge translational and clinical research by : Alexis Netis Simpkins
Download or read book Big data analytics to advance stroke and cerebrovascular disease: A tool to bridge translational and clinical research written by Alexis Netis Simpkins and published by Frontiers Media SA. This book was released on 2023-12-26 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning and Deep Learning in Neuroimaging Data Analysis by : Anitha S. Pillai
Download or read book Machine Learning and Deep Learning in Neuroimaging Data Analysis written by Anitha S. Pillai and published by CRC Press. This book was released on 2024-02-15 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) and deep learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high-dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together artificial intelligence (AI) experts as well as medical practitioners, these chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research.
Book Synopsis Machine Learning and Decision Support in Stroke by : Fabien Scalzo
Download or read book Machine Learning and Decision Support in Stroke written by Fabien Scalzo and published by Frontiers Media SA. This book was released on 2020-07-09 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine learning and data science in heart failure and stroke by : Leonardo Roever
Download or read book Machine learning and data science in heart failure and stroke written by Leonardo Roever and published by Frontiers Media SA. This book was released on 2023-09-07 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Omics-Based Approaches in Stroke Research by : Shubham Misra
Download or read book Omics-Based Approaches in Stroke Research written by Shubham Misra and published by Frontiers Media SA. This book was released on 2024-08-23 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Omics-based approaches have emerged as powerful tools in stroke research, revolutionizing our understanding of the underlying molecular mechanisms and potential therapeutic targets. These approaches encompass various disciplines such as genomics, transcriptomics, proteomics, metabolomics, radiomics, and epigenomics, enabling comprehensive analysis of biological and imaging markers and their interactions. Through genomics, researchers can identify genetic variants associated with stroke susceptibility, offering insights into individual risk factors and personalized medicine. Transcriptomics allows the investigation of gene expression patterns, highlighting key molecular pathways involved in stroke pathology and providing potential targets for intervention. Proteomics aids in the identification and quantification of proteins associated with stroke, aiding in the discovery of novel biomarkers and therapeutic targets. Metabolomics explores the metabolites involved in stroke pathophysiology, shedding light on metabolic alterations and potential therapeutic strategies. Radiomics involves the extraction and analysis of a multitude of quantitative features from medical imaging data, such as CT or MRI scans serving as potential imaging biomarkers, contributing to risk stratification and the identification of novel insights into stroke pathophysiology. Finally, epigenomics investigates modifications in gene expression without changing the DNA sequence, uncovering epigenetic mechanisms underlying stroke susceptibility and recovery. By integrating and analyzing data from these omics platforms, researchers can gain a comprehensive understanding of stroke pathogenesis, paving the way for the development of innovative diagnostic tools and effective therapeutic interventions.
Book Synopsis The application of artificial intelligence in interventional neuroradiology by : Yuhua Jiang
Download or read book The application of artificial intelligence in interventional neuroradiology written by Yuhua Jiang and published by Frontiers Media SA. This book was released on 2023-07-03 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning in Action: Stroke Diagnosis and Outcome Prediction by : Ramin Zand
Download or read book Machine Learning in Action: Stroke Diagnosis and Outcome Prediction written by Ramin Zand and published by Frontiers Media SA. This book was released on 2022-08-18 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Medical Image Understanding and Analysis by : Bartłomiej W. Papież
Download or read book Medical Image Understanding and Analysis written by Bartłomiej W. Papież and published by Springer Nature. This book was released on 2020-07-08 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 24th Conference on Medical Image Understanding and Analysis, MIUA 2020, held in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 29 full papers and 5 short papers presented were carefully reviewed and selected from 70 submissions. They were organized according to following topical sections: image segmentation; image registration, reconstruction and enhancement; radiomics, predictive models, and quantitative imaging biomarkers; ocular imaging analysis; biomedical simulation and modelling.
Book Synopsis Intelligent Diagnosis with Adversarial Machine Learning in Multimodal Biomedical Brain Images by : Yuhui Zheng
Download or read book Intelligent Diagnosis with Adversarial Machine Learning in Multimodal Biomedical Brain Images written by Yuhui Zheng and published by Frontiers Media SA. This book was released on 2021-09-23 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Combination of Data-Driven Machine Learning Approaches and Prior Knowledge for Robust Medical Image Processing and Analysis by : Jinming Duan
Download or read book The Combination of Data-Driven Machine Learning Approaches and Prior Knowledge for Robust Medical Image Processing and Analysis written by Jinming Duan and published by Frontiers Media SA. This book was released on 2024-06-11 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the availability of big image datasets and state-of-the-art computing hardware, data-driven machine learning approaches, particularly deep learning, have been used in numerous medical image (CT-scans, MRI, PET, SPECT, etc..) computing tasks, ranging from image reconstruction, super-resolution, segmentation, registration all the way to disease classification and survival prediction. However, training such high-precision approaches often require large amounts of data to be collected and labelled and high-capacity graphics processing units (GPUs) installed, which are resource intensive and hence not always practical. Other hurdles such as the generalization ability to unseen new data and difficulty to interpret and explain can prevent their deployment to those clinical applications which deem such abilities imperative.
Book Synopsis Machine Learning-Assisted Diagnosis and Treatment of Endocrine-Related Diseases by : Qiuming Yao
Download or read book Machine Learning-Assisted Diagnosis and Treatment of Endocrine-Related Diseases written by Qiuming Yao and published by Frontiers Media SA. This book was released on 2023-12-27 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence in Medicine by : Niklas Lidströmer
Download or read book Artificial Intelligence in Medicine written by Niklas Lidströmer and published by Springer. This book was released on 2022-03-17 with total page 1816 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a structured and analytical guide to the use of artificial intelligence in medicine. Covering all areas within medicine, the chapters give a systemic review of the history, scientific foundations, present advances, potential trends, and future challenges of artificial intelligence within a healthcare setting. Artificial Intelligence in Medicine aims to give readers the required knowledge to apply artificial intelligence to clinical practice. The book is relevant to medical students, specialist doctors, and researchers whose work will be affected by artificial intelligence.
Book Synopsis Data Science in the Medical Field by : Seifedine Kadry
Download or read book Data Science in the Medical Field written by Seifedine Kadry and published by Elsevier. This book was released on 2024-09-30 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: ata science has the potential to influence and improve fundamental services such as the healthcare sector. This book recognizes this fact by analyzing the potential uses of data science in healthcare. Every human body produces 2 TB of data each day. This information covers brain activity, stress level, heart rate, blood sugar level, and many other things. More sophisticated technology, such as data science, allows clinicians and researchers to handle such a massive volume of data to track the health of patients. The book focuses on the potential and the tools of data science to identify the signs of illness at an extremely early stage. • Shows how improving automated analytical techniques can be used to generate new information from data for healthcare applications• Combines a number of related fields, with a particular emphasis on machine learning, big data analytics, statistics, pattern recognition, computer vision, and semantic web technologies• Provides information on the cutting-edge data science tools required to accelerate innovation for healthcare organizations and patients by reading this book
Book Synopsis Bio-inspired Neurocomputing by : Akash Kumar Bhoi
Download or read book Bio-inspired Neurocomputing written by Akash Kumar Bhoi and published by Springer Nature. This book was released on 2020-07-21 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchers as well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.
Book Synopsis Decision Support in Clinical Practice for Stroke: Clinician Experiences and Expectations by : Andrew Bivard
Download or read book Decision Support in Clinical Practice for Stroke: Clinician Experiences and Expectations written by Andrew Bivard and published by Frontiers Media SA. This book was released on 2021-07-01 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Prediction in Medicine: The Impact of Machine Learning on Healthcare by : Neeta Verma
Download or read book Prediction in Medicine: The Impact of Machine Learning on Healthcare written by Neeta Verma and published by Bentham Science Publishers. This book was released on 2024-10-11 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prediction in Medicine: The Impact of Machine Learning on Healthcare explores the transformative power of advanced data analytics and machine learning in healthcare. This comprehensive guide covers predictive analysis, leveraging electronic health records (EHRs) and wearable devices to optimize patient care and healthcare planning. Key topics include disease diagnosis, risk assessment, and precision medicine advancements in cardiovascular health and hypertension management. The book also addresses challenges in interpreting clinical data and navigating ethical considerations. It examines the role of AI in healthcare emergencies and infectious disease management, highlighting the integration of diverse data sources like medical imaging and genomic data. Prediction in Medicine is essential for students, researchers, healthcare professionals, and general readers interested in the future of healthcare and technological innovation.
