Venkataraman Lakshmi – författare & böcker

P. Mohamed Fathimal, T. Ganesh Kumar, J. B. Shajilin Loret, Venkataraman Lakshmi, Manish T. I. - Advances of Machine Learning for Knowledge Mining in Electronic Health Records, Inbunden

Advances of Machine Learning for Knowledge Mining in Electronic Health Records

AvP. Mohamed Fathimal,T. Ganesh Kumarm. fl.

Inbunden, Engelska, 2025

2 319 kr

Skickas inom 10-15 vardagar

The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR consisting of demographics, medical history, and diagnosis, with a focus on the design and representation of structured, semi-structured, and unstructured data.Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health recordsCovers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured dataDiscusses supervised and unsupervised learning in electronic health recordsDescribes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health recordsThis book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning.

Nyhet

Advances of Machine Learning for Knowledge Mining in Electronic Health Records

AvP. Mohamed Fathimal,T. Ganesh Kumarm. fl.

Häftad, Engelska, 2026

758 kr

Skickas inom 10-15 vardagar

The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR consisting of demographics, medical history, and diagnosis, with a focus on the design and representation of structured, semi-structured, and unstructured data.Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health recordsCovers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured dataDiscusses supervised and unsupervised learning in electronic health recordsDescribes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health recordsThis book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning.

Manish T. I., Venkataraman Lakshmi, J. B. Shajilin Loret, T. Ganesh Kumar, P. Mohamed Fathimal - Advances of Machine Learning for Knowledge Mining in Electronic Health Records, E-bok

Advances of Machine Learning for Knowledge Mining in Electronic Health Records

AvManish T. I.,Venkataraman Lakshmim. fl.

E-bok

PDF, Engelska, 2025

2 673 kr

Läs direkt efter köp

The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR consisting of demographics, medical history, and diagnosis, with a focus on the design and representation of structured, semi-structured, and unstructured data.

Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health records Covers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured data Discusses supervised and unsupervised learning in electronic health records Describes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health records

This book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning.

Advances of Machine Learning for Knowledge Mining in Electronic Health Records

AvManish T. I.,Venkataraman Lakshmim. fl.

E-bok

Engelska, 2025

2 697 kr

Läs direkt efter köp

The book explores the application of cutting-edge machine learning and deep learning algorithms in mining Electronic Health Records (EHR). With the aim of improving patient health management, this book explains the structure of EHR consisting of demographics, medical history, and diagnosis, with a focus on the design and representation of structured, semi-structured, and unstructured data.

Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health records Covers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured data Discusses supervised and unsupervised learning in electronic health records Describes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health records

This book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning.

Del 3 - Water Science and Application

Land Surface Hydrology, Meteorology, and Climate

Observations and Modeling

AvVenkataraman Lakshmi,John Albertsonm. fl.

Inbunden, Engelska, 2001

811 kr

Tillfälligt slut

Published by the American Geophysical Union as part of the Water Science and Application Series, Volume 3.Land surface hydrology integrates various physical, chemical and biological processes that occur above, on, and below the surface of the Earth. As a result, it is critical to accurately account for land surface processes within predictive models of hydrology, meteorology, and climate.One of our main difficulties, however, concerns the broad range of spatial and temporal scales that characterize land surface hydrological processes. For example, we determine infiltration by pore scale physics, while soil hydraulic conductivity remains a field scale property. Photosynthesis, respiration, and transpiration occur at the leaf scale. Runoff is a catchment scale process, and the variability of groundwater storage is a regional scale issue. Turbulence in land-atmosphere exchanges of heat, moisture, and momentum occur on the order of seconds to minutes, while variations in land surface and air temperatures occur much more gradually: on the order of hours. The persistence of floods and droughts is seasonal to annual, and so is the effect of El Nino on regional hydrology. Long-term climate effects occur much more slowly, on the order of years to decades.

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Venkataraman Lakshmi – författare

Advances of Machine Learning for Knowledge Mining in Electronic Health Records

Advances of Machine Learning for Knowledge Mining in Electronic Health Records

Advances of Machine Learning for Knowledge Mining in Electronic Health Records

Advances of Machine Learning for Knowledge Mining in Electronic Health Records

Land Surface Hydrology, Meteorology, and Climate

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