9789811920561 - Prognostic Models in Healthcare: AI and Statistical Approaches: 109 (Studies in Big Data, 109) (11 resultados)

Condición: good. A book that has been read but is in overall good condition. Very minimal wear damage to the cover including scuff marks, but no major holes or tears. The dust jacket if applicable may not be included. Binding may have minimal wear. The majority of pages are undamaged with minimal creasing or tearing. May have minimal pencil underlining and or highlighting of text and possible small amounts of writing. No missing pages. May have some light marks on the page edges or a remainder mark. May have pale yellow yellowed pages. Fast Shipping, safe and secure mailers. Stock photo used.

Condición: New. In.

Hardcover. Condición: new. Hardcover. This book focuses on contemporary technologies and research in computational intelligence that has reached the practical level and is now accessible in preclinical and clinical settings. This book's principal objective is to thoroughly understand significant technological breakthroughs and research results in predictive modeling in healthcare imaging and data analysis. Machine learning and deep learning could be used to fully automate the diagnosis and prognosis of patients in medical fields. The healthcare industry's emphasis has evolved from a clinical-centric to a patient-centric model. However, it is still facing several technical, computational, and ethical challenges. Big data analytics in health care is becoming a revolution in technical as well as societal well-being viewpoints. Moreover, in this age of big data, there is increased access to massive amounts of regularly gathered data from the healthcare industry that has necessitated the development of predictive models and automated solutions for the early identification of critical and chronic illnesses. The book contains high-quality, original work that will assist readers in realizing novel applications and contexts for deep learning architectures and algorithms, making it an indispensable reference guide for academic researchers, professionals, industrial software engineers, and innovative model developers in healthcare industry. Moreover, in this age of big data, there is increased access to massive amounts of regularly gathered data from the healthcare industry that has necessitated the development of predictive models and automated solutions for the early identification of critical and chronic illnesses. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condición: New.

Condición: As New. Unread book in perfect condition.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on contemporary technologies and research in computational intelligence that has reached the practical level and is now accessible in preclinical and clinical settings. This book's principal objective is to thoroughly understand significant technological breakthroughs and research results in predictive modeling in healthcare imaging and data analysis. Machine learning and deep learning could be used to fully automate the diagnosis and prognosis of patients in medical fields. The healthcare industry's emphasis has evolved from a clinical-centric to a patient-centric model. However, it is still facing several technical, computational, and ethical challenges. Big data analytics in health care is becoming a revolution in technical as well as societal well-being viewpoints. Moreover, in this age of big data, there is increased access to massive amounts of regularly gathered data from the healthcare industry that has necessitated the development of predictive models and automated solutions for the early identification of critical and chronic illnesses. The book contains high-quality, original work that will assist readers in realizing novel applications and contexts for deep learning architectures and algorithms, making it an indispensable reference guide for academic researchers, professionals, industrial software engineers, and innovative model developers in healthcare industry.

Hardcover. Condición: new. Hardcover. This book focuses on contemporary technologies and research in computational intelligence that has reached the practical level and is now accessible in preclinical and clinical settings. This book's principal objective is to thoroughly understand significant technological breakthroughs and research results in predictive modeling in healthcare imaging and data analysis. Machine learning and deep learning could be used to fully automate the diagnosis and prognosis of patients in medical fields. The healthcare industry's emphasis has evolved from a clinical-centric to a patient-centric model. However, it is still facing several technical, computational, and ethical challenges. Big data analytics in health care is becoming a revolution in technical as well as societal well-being viewpoints. Moreover, in this age of big data, there is increased access to massive amounts of regularly gathered data from the healthcare industry that has necessitated the development of predictive models and automated solutions for the early identification of critical and chronic illnesses. The book contains high-quality, original work that will assist readers in realizing novel applications and contexts for deep learning architectures and algorithms, making it an indispensable reference guide for academic researchers, professionals, industrial software engineers, and innovative model developers in healthcare industry. Moreover, in this age of big data, there is increased access to massive amounts of regularly gathered data from the healthcare industry that has necessitated the development of predictive models and automated solutions for the early identification of critical and chronic illnesses. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Condición: Brand New. 526 pages. 9.25x6.10x1.13 inches. In Stock. This item is printed on demand.

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book focuses on contemporary technologies and research in computational intelligence that has reached the practical level and is now accessible in preclinical and clinical settings. This book s principal objective is to thoroughly understand significan.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book focuses on contemporary technologies and research in computational intelligence that has reached the practical level and is now accessible in preclinical and clinical settings. This book's principal objective is to thoroughly understand significant technological breakthroughs and research results in predictive modeling in healthcare imaging and data analysis. Machine learning and deep learning could be used to fully automate the diagnosis and prognosis of patients in medical fields. The healthcare industry's emphasis has evolved from a clinical-centric to a patient-centric model. However, it is still facing several technical, computational, and ethical challenges. Big data analytics in health care is becoming a revolution in technical as well as societal well-being viewpoints. Moreover, in this age of big data, there is increased access to massive amounts of regularly gathered data from the healthcare industry that has necessitated the development of predictive models and automated solutions for the early identification of critical and chronic illnesses. The book contains high-quality, original work that will assist readers in realizing novel applications and contexts for deep learning architectures and algorithms, making it an indispensable reference guide for academic researchers, professionals, industrial software engineers, and innovative model developers in healthcare industry. 528 pp. Englisch.

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -¿Segmentation of White Blood Cells in Acute Myeloid Leukaemia Microscopic Images: The Current Challenges and Future Solutions.- Computer Vision Based Prognostic Modeling of COVID-19 from Medical Imaging.- Skin Lesion Classification From Dermoscopic Images with Deep Residual Network based Fused Pigmented Deep Feature Extraction and Entropy Based Best Features Selection Approach.- Computer Vision Technologies for COVID-19 Prediction, Diagnosis and Prevention.- Health monitoring methods in heart diseases based on data mining approach, a directional survey.- Machine learning based brain diseases diagnosing in electroencephalogram signals, Alzheimer and Parkinson's.- Skin Lesion Detection Using Recent Machine Learning Approaches.- Improving monitoring and controling parameters for Alzheimer's patients based on IoT.- A Novel Method for Lung Segmentation of Chest with Convolutional Neural Network.- Leukemia Detection Using Machine and Deep Learning Through Microscopic Images-A Review.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 528 pp. Englisch.