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COVID-19 = prediction, decision-maki...
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Santosh, K. C.
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COVID-19 = prediction, decision-making, and its impacts /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
COVID-19/ edited by K. C. Santosh, Amit Joshi.
其他題名:
prediction, decision-making, and its impacts /
其他作者:
Santosh, K. C.
出版者:
Singapore :Springer Singapore : : 2021.,
面頁冊數:
xii, 137 p. :ill., digital ;24 cm.
內容註:
AI Joins the Fight Against COVID-19 -- AI for COVID-19: Conduits for Public Health Surveillance -- A Pre-screening Approach for COVID 19 Testing based on Belief Rule-Based Expert System -- Local Analytical System for Early Epidemic Detection -- Implementing early detection system for Covid-19 using anomaly detection -- Covid-19 classification based on Gray-Level Co-Occurrence Matrix and Support Vector Machine -- Rough sets in COVID-19 to Predict Symptomatic Cases -- COVID-19 Detection via Wavelet Entropy and Biogeography-based Optimization -- Machine Learning in Fighting Pandemics: A COVID-19 Case Study -- Robotics in Healthcare Against COVID-19 -- COVID-19: A necessity for changes and innovations -- Prediction to Service Delivery: AI in Action -- COVID-19 impacts construction industry: then, now, and future -- COVID-19 on Air Quality Index (AQI): A necessary evil?
Contained By:
Springer Nature eBook
標題:
COVID-19 (Disease) - Data processing. -
電子資源:
https://doi.org/10.1007/978-981-15-9682-7
ISBN:
9789811596827
COVID-19 = prediction, decision-making, and its impacts /
COVID-19
prediction, decision-making, and its impacts /[electronic resource] :edited by K. C. Santosh, Amit Joshi. - Singapore :Springer Singapore :2021. - xii, 137 p. :ill., digital ;24 cm. - Lecture notes on data engineering and communications technologies,v.602367-4512 ;. - Lecture notes on data engineering and communications technologies ;v.60..
AI Joins the Fight Against COVID-19 -- AI for COVID-19: Conduits for Public Health Surveillance -- A Pre-screening Approach for COVID 19 Testing based on Belief Rule-Based Expert System -- Local Analytical System for Early Epidemic Detection -- Implementing early detection system for Covid-19 using anomaly detection -- Covid-19 classification based on Gray-Level Co-Occurrence Matrix and Support Vector Machine -- Rough sets in COVID-19 to Predict Symptomatic Cases -- COVID-19 Detection via Wavelet Entropy and Biogeography-based Optimization -- Machine Learning in Fighting Pandemics: A COVID-19 Case Study -- Robotics in Healthcare Against COVID-19 -- COVID-19: A necessity for changes and innovations -- Prediction to Service Delivery: AI in Action -- COVID-19 impacts construction industry: then, now, and future -- COVID-19 on Air Quality Index (AQI): A necessary evil?
This book outlines artificial intelligence for COVID-19 issues that are ranging from prediction to decision-making for healthcare support in human lives. Starting with major COVID-19 issues and challenges, it takes possible AI-based solutions for multiple problems, such as early prediction, its role for public health, detection of positive cases, drug analysis, and healthcare support. It mainly employs publicly available data (population) to predict who should be tested for COVID-19, for example, radiological image data to detect COVID-19 positive cases from other similar and/or different manifestations, such as pneumonia, distributed healthcare support, and supply chains in the middle of COVID-19 pandemic. The book includes recently developed AI-driven tools and techniques, such as pattern recognition, anomaly detection, machine learning, and data analytics. It covers a wide range of audience from computer science and engineering to healthcare professionals.
ISBN: 9789811596827
Standard No.: 10.1007/978-981-15-9682-7doiSubjects--Topical Terms:
3486187
COVID-19 (Disease)
--Data processing.
LC Class. No.: RA644.C67
Dewey Class. No.: 616.2414
COVID-19 = prediction, decision-making, and its impacts /
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AI Joins the Fight Against COVID-19 -- AI for COVID-19: Conduits for Public Health Surveillance -- A Pre-screening Approach for COVID 19 Testing based on Belief Rule-Based Expert System -- Local Analytical System for Early Epidemic Detection -- Implementing early detection system for Covid-19 using anomaly detection -- Covid-19 classification based on Gray-Level Co-Occurrence Matrix and Support Vector Machine -- Rough sets in COVID-19 to Predict Symptomatic Cases -- COVID-19 Detection via Wavelet Entropy and Biogeography-based Optimization -- Machine Learning in Fighting Pandemics: A COVID-19 Case Study -- Robotics in Healthcare Against COVID-19 -- COVID-19: A necessity for changes and innovations -- Prediction to Service Delivery: AI in Action -- COVID-19 impacts construction industry: then, now, and future -- COVID-19 on Air Quality Index (AQI): A necessary evil?
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This book outlines artificial intelligence for COVID-19 issues that are ranging from prediction to decision-making for healthcare support in human lives. Starting with major COVID-19 issues and challenges, it takes possible AI-based solutions for multiple problems, such as early prediction, its role for public health, detection of positive cases, drug analysis, and healthcare support. It mainly employs publicly available data (population) to predict who should be tested for COVID-19, for example, radiological image data to detect COVID-19 positive cases from other similar and/or different manifestations, such as pneumonia, distributed healthcare support, and supply chains in the middle of COVID-19 pandemic. The book includes recently developed AI-driven tools and techniques, such as pattern recognition, anomaly detection, machine learning, and data analytics. It covers a wide range of audience from computer science and engineering to healthcare professionals.
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