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The Implementation of AI and AI-Empowered Imaging System to Fight Against COVID-19—A Review Implementation of Machine Learning Techniques for the Analysis of Transmission Dynamics of COVID-19 Data-Driven Decision Making in IoT Healthcare Systems—COVID-19: A Case Study Touch and Voice-Assisted Multilingual Communication Prototype for ICU Patients Specific to COVID’19 Cerebral Venous Thrombosis post BNT162b2 mRNA SARS-CoV-2 vaccination: A Black Swan Event
Smart Healthcare System Design ; n/a(n/a):301-311, 2021.
Article in English | Wiley | ID: covidwho-1272154
ABSTRACT
Summary COVID-19 has already affected the world with this deadly virus, resulting in over 3.5 lakh deaths. The behavior of this virus is extraordinarily peculiar and mutates frequently. So, the scientific community faces the problems to analyze and forecast the virus's growth and transmission capability. The combined effort of powerful Artificial intelligence and Image processing techniques to predict the initial pattern of COVID-19 disease identifies the most affected areas in each country through social networking information and predicts drug-protein interactions for making new drugs vaccines. However, AI-empowered X-Ray and computed tomography image acquisition and segmentation techniques help us identify and diagnose the COVID-19 affected patients with minimal contact. In this chapter, our primary motivation is to sum up the essential roles of some AI-driven techniques (Machine learning, Deep learning, etc.) and AI-empowered imaging techniques to analyze, predict, and diagnose against COVID-19 disease. An essential set of open challenges and future research issues on AI-empowered procedures for handling COVID-19 are also discussed in this chapter. Summary This paper mainly deals with the design of Machine Learning model for the analysis of transmission dynamics of Covid 19. The entire globe is affected because of Corona virus. Ventilator dependent, Severe Acute respiratory and quarantine care ICU patients frequently face difficulties for their most basic human interactions, namely communication due to either respiratory illness, language problem or intubated. ICU patients have serious implications with respect to physical and psychological due to non communication problems. Researchers have developed different types of services like Speech language Pathologist so that Augmentative and alternative communication assistance can be given to all health professionals and caretakers. A probabilistic model is designed to analyse the new cases and death cases. Using machine learning approach Regression model is designed and future predications are displayed. The adequacy of the model is discussed along with the residuals of new cased and death cases. PCF and APCAF are obtained. This paper mainly deals with a probabilistic model to analyse and predict the new cases and deaths of covid 19. A new transformation of analyzing stationarity is carried out and based on this forecasting is executed. Summary This research express an impression of automated decision-making techniques that have been suggested for scrutiny of data from IoT based healthcare systems. IoT data analytics plays a vital role in this modern era since data from connected devices reveal meaningful results with better insights for the future. The chapter involves the design of a decision-making system that collects data from IoT based healthcare systems, preprocess and analyzes data, and generates detailed information reports for better diagnosis. Data preprocessing methods such as data cleaning, munging, normalization, reduction, and removing noisy data are applied. The blend of IoT data with analytics technique results to be beneficial in healthcare systems. The collected IoT information like pulse rate, temperature, oxygen level and heart rate from connected devices can be used to analyze the need and severity in the preliminary stage itself using appropriate machine learning techniques. Multi Criteria Decision Making (MCDM) techniques such as SMART, WPM, and TOPSIS are also applied for conclusion production procedure to generate detailed informative diagnostic reports. Being healthcare data, the overall objective is to aid business organizations with better decision making processes through data analytics thereby deploying the right IoT strategy. The result of the next-generation expert systems can utilize the results for further analysis in diagnosis and treatment. Summary The proposed work deals with the design and development of touch and native voice-assisted prototype to enable the intuitive communication & interaction between health professionals and patients who are affected with Severe Acute Respiratory Infection (SARI), Ventilator-dependent and admitted in Quarantine care. It also ensures the development of the multilingual capability to communicate effectively in most speaking ten Indian languages, so that the patients will be relieved from pains etc., as their queries are being addressed by health professionals. In this prototype, touch based gesture patterns can be effectively used as an interactive module and helps the doctors to monitor and answer to the queries of ICU patients regularly by updating it to the caretakers such that the patients are at ease to express their emotions or pains. The proposed prototype will be made available and accessible in an open software repository. As per the existing methods patients express their needs through non-verbal communication methods and they could be missed out or misinterpreted resulting in symptoms that are poorly understood and the clinicians overestimate their ability to understand their communication feelings. These situations are eradicated by employing the use of ?Touch Voice of SARI? Application. Hence this can be considered as an assistive communication tool which replaces the nonverbal communication to a meaningful communication for ventilator patients and healthcare professionals.

Full text: Available Collection: Databases of international organizations Database: Wiley Type of study: Case report Topics: Vaccines Language: English Journal: Smart Healthcare System Design Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Wiley Type of study: Case report Topics: Vaccines Language: English Journal: Smart Healthcare System Design Year: 2021 Document Type: Article