9781779643186 - Machine Learning Applications for Data Analysis in Healthcare Systems (15 resultados)

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Condición: As New. Unread book in perfect condition.

Condición: As New. Unread book in perfect condition.

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Hardcover. Condición: Brand New. 222 pages. 9.18x6.12x9.00 inches. In Stock.

Hardcover. Condición: new. Hardcover. This comprehensive exploration investigates the powerful intersection and the ever-changing impact of machine learning techniques on data analysis in healthcare, transforming the way we approach medical challenges, improve patient outcomes, and enhance healthcare systems. The healthcare industry generates an enormous amount of data, from electronic health records and medical imaging to genomic sequencing and wearable devices. However, the true value of this data lies not in its sheer volume but in the insights it can provide. Machine learning algorithms offer the means to unlock the hidden patterns and knowledge within this data, enabling us to make informed decisions, identify high-risk patients, and personalize interventions for better healthcare outcomes. This volume emphasizes the practical implementation of machine learning techniques, supported by real-world case studies and examples. Discusses machine learning and its potential in outbreak prediction, design and development of anti-cancerous drug molecules. Delves into heartbeat classification based on a machine-human interaction model. Looks at role of machine learning in clinical decision-making, predictive modeling, public health management, and more. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condición: new. Hardcover. This comprehensive exploration investigates the powerful intersection and the ever-changing impact of machine learning techniques on data analysis in healthcare, transforming the way we approach medical challenges, improve patient outcomes, and enhance healthcare systems. The healthcare industry generates an enormous amount of data, from electronic health records and medical imaging to genomic sequencing and wearable devices. However, the true value of this data lies not in its sheer volume but in the insights it can provide. Machine learning algorithms offer the means to unlock the hidden patterns and knowledge within this data, enabling us to make informed decisions, identify high-risk patients, and personalize interventions for better healthcare outcomes. This volume emphasizes the practical implementation of machine learning techniques, supported by real-world case studies and examples. Discusses machine learning and its potential in outbreak prediction, design and development of anti-cancerous drug molecules. Delves into heartbeat classification based on a machine-human interaction model. Looks at role of machine learning in clinical decision-making, predictive modeling, public health management, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Condición: new. Hardcover. This comprehensive exploration investigates the powerful intersection and the ever-changing impact of machine learning techniques on data analysis in healthcare, transforming the way we approach medical challenges, improve patient outcomes, and enhance healthcare systems. The healthcare industry generates an enormous amount of data, from electronic health records and medical imaging to genomic sequencing and wearable devices. However, the true value of this data lies not in its sheer volume but in the insights it can provide. Machine learning algorithms offer the means to unlock the hidden patterns and knowledge within this data, enabling us to make informed decisions, identify high-risk patients, and personalize interventions for better healthcare outcomes. This volume emphasizes the practical implementation of machine learning techniques, supported by real-world case studies and examples. Discusses machine learning and its potential in outbreak prediction, design and development of anti-cancerous drug molecules. Delves into heartbeat classification based on a machine-human interaction model. Looks at role of machine learning in clinical decision-making, predictive modeling, public health management, and more. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This comprehensive exploration investigates the powerful intersection and the ever-changing impact of machine learning techniques on data analysis in healthcare, transforming the way we approach medical challenges, improve patient outcomes, and enhance healthcare systems. The healthcare industry generates an enormous amount of data, from electronic health records and medical imaging to genomic sequencing and wearable devices. However, the true value of this data lies not in its sheer volume but in the insights it can provide. Machine learning algorithms offer the means to unlock the hidden patterns and knowledge within this data, enabling us to make informed decisions, identify high-risk patients, and personalize interventions for better healthcare outcomes. This volume emphasizes the practical implementation of machine learning techniques, supported by real-world case studies and examples.