Murugeswari (77 résultats)

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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

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paperback. Etat : New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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Paperback. Etat : New. Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data.Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient's medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process.Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.…

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Paperback / softback. Etat : New. New copy - Usually dispatched within 4 working days.

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Paperback. Etat : New. Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data.Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient's medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process.Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.…

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Taschenbuch. Etat : Neu. Feeding of Tapioca (Manihot esculenta crantz) Leaves to Ruminants | STUDIES ON THE EFFECT OF TAPIOCA (Manihot esculenta crantz) LEAVES ON RUMEN FERMENTATION | Murugeswari R. (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786204744582 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Etat : New. Dr. K. Murugeswari is a Senior Assistant Professor in the School of Computing Science and Engineering at VIT Bhopal University, M.P, India.Dr. B. Sundaravadivazhagan is a professor in the Department of Information.

Paperback. Etat : Brand New. 308 pages. 9.18x6.12x9.21 inches. In Stock.

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Taschenbuch. Etat : Neu. A Textbook of Modern Physics | R. Murugeswari (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209650543 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Taschenbuch. Etat : Neu. MODERN TECHNIQUE TO ENHANCE THE EFFICIENCY OF SMART GRID | An Ultimate Solution to Improve Smart Grid Efficiency | P. Murugeswari (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209619960 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Paperback. Etat : New. Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data.Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient's medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process.Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.…

Paperback. Etat : new. Paperback. Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data.Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patients medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process.Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes. The book is a baseline reference for researchers and academicians who are investigating the application of deep learning algorithms in the healthcare sector. It focuses on medical imaging and healthcare data analytics. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Paperback. Etat : New. Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data.Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient's medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process.Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.…