Mathur Manish (36 results)

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Paperback. Condition: New. Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare.Authors Kerrie Holley and Manish Mathur from Google's Healthcare and Life Sciences Industry team help you explore real-world applications of these technologies in healthcare, from personalized patient care and drug discovery to enhanced medical imaging and robot-assisted surgeries. You'll also learn the challenges of using these technologies-and the ethical implications of their application in this field.With this book, you will:Learn how LLMs and generative AI can help address and transform healthcare issuesExplore the basics of LLMs and generative AI and learn how they workLearn how these technologies are being applied in healthcare todayUnderstand several LLM and generative AI use casesExamine the ethics and challenges of applying LLMs and generative AI to healthcareUnderstand the potential use of LLMs and generative AI in healthcare in the near term and their prospects for the future.

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Paperback. Condition: New. Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare.Authors Kerrie Holley and Manish Mathur from Google's Healthcare and Life Sciences Industry team help you explore real-world applications of these technologies in healthcare, from personalized patient care and drug discovery to enhanced medical imaging and robot-assisted surgeries. You'll also learn the challenges of using these technologies-and the ethical implications of their application in this field.With this book, you will:Learn how LLMs and generative AI can help address and transform healthcare issuesExplore the basics of LLMs and generative AI and learn how they workLearn how these technologies are being applied in healthcare todayUnderstand several LLM and generative AI use casesExamine the ethics and challenges of applying LLMs and generative AI to healthcareUnderstand the potential use of LLMs and generative AI in healthcare in the near term and their prospects for the future.

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Hardcover. Condition: New. 1st Edition. Contents: Preface. 1. Concept of plant epidemic and its historical perspective. 2. Attributes of plant epidemic. 3. Mathematical modeling in botanical epidemiology. 4. Spatial patterns analysis in botanical epidemiology. 5. Plant disease forecasting and warning system s. 6. Approaches for epidemic avoidance. 7. Academic gains (short. descriptive and objective questions). Subject Index. A disease is said to be an epidemic when it occurs at very large geographically area and within a relatively shorter period of time. Appraisal of literature reveled that there is a gap about simplification of attributes of plant disease epidemiology for graduate and post-graduate students in the form of a text book. Thus, present book was intended to facilitate the reader acquaintance with subject portrayal. In present book the questions are formulated to provide an insight to the students and to researchers for their problem in hand and answers of formulated questions are transcendentally embedded in writing parts. Academic gain with this book also pertains to twelve practical exercise as well as explanation of some numerical problems. Global and Indian perspectives of plant disease epidemic, working examples (excel and mathematical part) for calculation of AUDPC, rAUDPC, DPC, sanitation ratio, disease severity, disease incidence, basic rate of infection, apparent rate of infection and economic injury level (EIL) along with other international indexes like Panicle Blast Severity (PBS index), simplified version of mathematical modelling for botanical epidemiology that includes compartmental models, basic SIR s and its variants, sample size determination, binomial, the Bayesian approaches and the ordination analysis, concepts of disease forecasting, warning, predictive system, aerobiology and computer simulations, approaches of epidemic avoidance like cultural, gene pyramiding, gene deployment, multiline, protein for protein hypothesis, gene for gene hypothesis, the vertifolia affect, inoculums potential and short and descriptive questions along with multiple choice questions with key are the major highlights of this book.

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Condition: New. 2024. 1st Edition. paperback. . . . . .

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Paperback. Condition: Brand New. 200 pages. 9.19x7.00x9.19 inches. In Stock.

Hardcover. Condition: New. Dust Jacket Condition: New. 1st Edition. Contents: 1. Tools for detecting spatial pattern. 2. Spatial autocorrelation. 3. Methods of edge correction. 4. Factors affecting spatial distribution. 5. Consequences of spatial patterns. Glossary. This book pertaining the up-to date information related with different approaches for spatial data analysis. The book consists five different chapters that deal with various tools available for spatial data analysis, spatial auto-correlation, edge correction, various abiotic and biotic factors that affecting spatial distribution and consequences of spatial pattern. At the end of the book around thirty six questions are also presented that need to be solved. For better understanding of the various equations presented in this book, a list a various symbols and their examples also provided.

Condition: New. 2024. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.

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Hardcover. Condition: New. ISBN:9788170195405.

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Paperback. Condition: New. Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare.Authors Kerrie Holley and Manish Mathur from Google's Healthcare and Life Sciences Industry team help you explore real-world applications of these technologies in healthcare, from personalized patient care and drug discovery to enhanced medical imaging and robot-assisted surgeries. You'll also learn the challenges of using these technologies-and the ethical implications of their application in this field.With this book, you will:Learn how LLMs and generative AI can help address and transform healthcare issuesExplore the basics of LLMs and generative AI and learn how they workLearn how these technologies are being applied in healthcare todayUnderstand several LLM and generative AI use casesExamine the ethics and challenges of applying LLMs and generative AI to healthcareUnderstand the potential use of LLMs and generative AI in healthcare in the near term and their prospects for the future.

Condition: New. &Uumlber den AutorKerrie Holley is currently the Director, Healthcare and Life sciences Industry Solutions, Google Cloud. Prior to this position, Kerrie joined United Health Group (UHG), Optum, as their first Technology Fellow and Senio.

Paperback. Condition: New. Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare.Authors Kerrie Holley and Manish Mathur from Google's Healthcare and Life Sciences Industry team help you explore real-world applications of these technologies in healthcare, from personalized patient care and drug discovery to enhanced medical imaging and robot-assisted surgeries. You'll also learn the challenges of using these technologies-and the ethical implications of their application in this field.With this book, you will:Learn how LLMs and generative AI can help address and transform healthcare issuesExplore the basics of LLMs and generative AI and learn how they workLearn how these technologies are being applied in healthcare todayUnderstand several LLM and generative AI use casesExamine the ethics and challenges of applying LLMs and generative AI to healthcareUnderstand the potential use of LLMs and generative AI in healthcare in the near term and their prospects for the future.

Hardcover. Condition: New. 1st Edition. Contents: 1. Fundaments of environmental impact assessment: meaning, history and objectives. 2. Attributes of EIA process. 3. EIA methodologies. 4. Environmental impact assessment for air environment. 5. EIA for water resources. 6. Environmental impact assessment of soil qualities. 7. Environmental impact assessment of noise. 8. Environmental impact assessment of biological components. 9. Traditional knowledge and impact assessment. 10. Impact assessment of socio-economic environment. 11. EIA implementation and follow-up. References. This book provides pin point information's linked with various attributes of EIA viz., related with their needs, historical developments, methods, important steps, role of various international and national organizations etc. First three chapter's deals with basics of EIA methodology and their protocol, comparative assessment of EIA's in various developed and developing countries, role of World Bank, Asian Development Bank, UNEP and MoEF. SWOFT analysis of EIA's in various sectors provided in chapter two. Chapter three relates with methodologies that comprises traditional EIA methods as well as some new approaches like TOPSIS, CBI, DPSIR etc. In additions, objectives, descriptions and web address of 20 different simulation models also presented. Reaming chapters (eight) deals with EIA in different sectors like transport, air, nose, biodiversity, socio-economic, soil, evaluation and traditional knowledge. For all these chapters quantitative approaches available in different research findings provided and interpreted sufficiently.