A study on the impact of data analytics in COVID-19 health care system

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Through the disperse of novel coronavirus illness globally, existence became considerably contrived. Data analytics have experienced powerful development over the past few years. As it happens, it’s exceptionally considerable to take advantage of data analytics to assist mankind in a prompt as well as factually precise method to forestall additionally restrain the advancement of the widespread, sustain gregarious balance and evaluate the influence of the widespread. The unforeseen significant number of coronavirus disease instances has disturbed medical care system in many economies furthermore eventuated in an insufficiency of dormitory in the hospices. For this reason, prognosticating quantity of coronavirus infection instances is indispensable for administrations to adopt the necessary measures. The count of coronavirus disease instances could be correctly anticipated by taking into account historical records of announced instances side by side few extraneous components that impact the disseminate of the COVID-19 . Hence, the principal aim out of this research is to contemporaneously consider historical data and the extraneous components. This paper explores how data analytics can play a role in health care especially in novel coronavirus illness.

Technology

Although the lungs are one of the most vital organs in the body, they are vulnerable to infection and injury. COVID-19 has put the entire world in an unprecedented difficult situation, bringing life to a halt and claiming thousands of lives all across the world. Medical imaging, such as X-rays and computed tomography (CT), is essential in the global fight against COVID-19, and newly emerging artificial intelligence (AI) technologies are boosting the power of imaging tools and assisting medical specialists. AI can improve job efficiency by precisely identifying infections in X-ray and CT images and allowing further measurement. We focus on the integration of AI with X-ray and CT, both of which are routinely used in frontline hospitals, to reflect the most recent progress in medical imaging and radiology combating COVID-19.

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Tuberculosis is the second leading cause of death from an infectious disease worldwide, after the human immunodeficiency virus. The main aim of this research work is to develop a Neuro-Fuzzy system for diagnosing tuberculosis. The system is structured with to accept symptoms with the help of three domain Medical expertise as inputs that are used to automatically generate rules that are injected in to the knowledge based where the system would use to make decisions and draw a conclusion. MATLAB 7.0 is used to implement this experiment using fuzzy logic and Neural Network toolbox. In this experiment linguistic variables are evaluated using Gaussian membership function. This system will offer potential assistance to medical practitioners and healthcare sector in making prompt decision during the diagnosis of tuberculosis. In this work basic emblematic approach using Neuro-fuzzy methodology is presented that describes a technique to forecast the existence of mycobacterium and provides support platform to researchers in the related field.

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Viral hepatitis is the regularly found health problem throughout the world among other easily transmitted diseases, such as tuberculosis, human immune virus, malaria and so on. Among all hepatitis viruses, the uppermost numbers of deaths are result from the long-lasting hepatitis C infection or long-lasting hepatitis B. In order to develop this system, the knowledge is acquired using both structured and semi-structured interviews from internists of St.Paul Hospital. Once the knowledge is acquired, it is modeled and represented using rule based reasoning techniques. Both forward and backward chaining is used to infer the rules and provide appropriate advices in the developed expert system. For the purpose of developing the prototype expert system SWI-prolog editor also used. The proposed system has the ability to adapt with dynamic knowledge by generalizing rules and discover new rules through learning the newly arrived knowledge from domain experts adaptively without any help from the knowledge engineer

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EHR Electronic Health Records collects data on yearly basis and it is used in many countries for healthcare.HER Health Examination Records collects the data on regular basis and identifies the participants at risk that is important for early warning and prevention.the fundamental challenge is for learning classification model for risk prediction with unlabelled data and live data string that established the majority of the collected dataset.the unlabelled data string describes the participants in health examintions whose health conditions can be vary from healthy to highly risky or very ill.in this paper, we propose a graph based,semisupervised learning algorithm called SHG health semi supervised heterogenous graph on Health for risk prediction and assessment to classify a progressively developing condition with the majority of the data unlabelled. An efficient iterative algorithm is designed and developed to proof the convergence is given.extensive experiments based on both real health examination dataset and live datasets to show effectiveness of our method. Jayashri A. Sonawane | Dr. Swati A. Bhavsar ""Mining Health Examination Records - A Graph Based Approach"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd22810.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/22810/mining-health-examination-records---a-graph-based-approach/jayashri-a-sonawane

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Classification and regression as data mining techniques for predicting the diseases outbreak has been permitted in the health institutions which have relative opportunities for conducting the treatment of diseases. But there is a need to develop a strong model for predicting disease outbreak in datasets based in various countries by filling the existing data mining technique gaps where the majority of models are relaying on single data mining techniques which their accuracies in prediction are not maximized for achieving expected results and also prediction are still few. This paper presents a survey and analysis for existing techniques on both classification and regression models techniques that have been applied for diseases outbreak prediction in datasets.

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Introduction: In recent years, the healthcare landscape in India has undergone a significant transformation, and at the forefront of this revolution is the rapidly growing telemedicine market. Telemedicine, the use of technology to provide healthcare remotely, has gained immense popularity, especially in a country as vast and diverse as India. This blog explores the dynamics, drivers, challenges, and future prospects of the India telemedicine market. Market Overview: The telemedicine market in India has witnessed unprecedented growth, fueled by advancements in technology, increasing internet penetration, and the need for accessible and affordable healthcare services. According to various reports, the market is expected to continue its upward trajectory in the coming years. Drivers of Telemedicine Growth: Digital Penetration: The widespread availability of smartphones and internet connectivity has opened doors for telemedicine to reach remote and underserved areas. People in rural and urban areas alike can now access healthcare services with just a few clicks on their smartphones. COVID-19 Pandemic: The global health crisis acted as a catalyst for the adoption of telemedicine. Social distancing norms and the fear of exposure to the virus prompted a surge in virtual consultations, making telemedicine a mainstream healthcare solution. Government Initiatives: The Indian government has recognized the potential of telemedicine in improving healthcare accessibility. Initiatives such as the Telemedicine Practice Guidelines and the National Digital Health Mission have laid the foundation for a structured and regulated telehealth ecosystem. Challenges and Solutions: Digital Divide: Despite the growth, challenges related to the digital divide persist. Rural areas often face issues such as poor internet connectivity and a lack of digital literacy. Addressing these challenges requires collaborative efforts from the government, private sector, and non-profit organizations. Data Security Concerns: Patient data security is a critical aspect of telemedicine. Ensuring robust cybersecurity measures, compliance with data protection laws, and creating awareness among users are essential steps in overcoming these concerns. Regulatory Framework: While the government has taken steps to regulate telemedicine, ongoing efforts are required to refine and adapt the regulatory framework to the evolving nature of the market. Striking a balance between innovation and patient safety is crucial. Key Players and Platforms: Several telemedicine platforms have emerged as key players in the Indian market. From established healthcare providers offering virtual consultations to dedicated telehealth startups, the landscape is diverse. Companies like Practo, Apollo 24/7, and Mfine are among those making significant contributions. Key Companies working on it includes Lybrate, mFine, myUpchar, vHealth, Zoylo Digihealth Pvt. Ltd., TeleVital, DocOnline, MedCords, 1Mg, M16 Labs, Artem Health,

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PHP Frameworks: I want to break free (IPC Berlin 2024)

Ralf Eggert

In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development. This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.

Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024

Tobias Schneck

As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other? Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.

Connector Corner: Automate dynamic content and events by pushing a button

DianaGray10

Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to: Create a campaign using Mailchimp with merge tags/fields Send an interactive Slack channel message (using buttons) Have the message received by managers and peers along with a test email for review But there’s more: In a second workflow supporting the same use case, you’ll see: Your campaign sent to target colleagues for approval If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team But—if the “Reject” button is pushed, colleagues will be alerted via Slack message Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors. And... Speakers: Akshay Agnihotri, Product Manager Charlie Greenberg, Host

Epistemic Interaction - tuning interfaces to provide information for AI support

Alan Dix

Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024 https://alandix.com/academic/papers/synergy2024-epistemic/ As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.

LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...

DanBrown980551

Do you want to learn how to model and simulate an electrical network from scratch in under an hour? Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)! During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook. PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides: - A fully editable and extendable library for grid component modelling; - Visualization tools to display your network; - Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses; The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well. What you will learn during the webinar: - For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills; - For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.

UiPath Test Automation using UiPath Test Suite series, part 4

DianaGray10

Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap. The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies. Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques What will you get from this session? 1. Insights into SAP testing best practices 2. Heatmap utilization for testing 3. Optimization of testing processes 4. Demo Topics covered: Execution from the test manager Orchestrator execution result Defect reporting SAP heatmap example with demo Speaker: Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP

FIDO Alliance Osaka Seminar: Overview.pdf

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Bits & Pixels using AI for Good.........

Alison B. Lowndes

Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...

UiPathCommunity

💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™: See how to accelerate model training and optimize model performance with active learning Learn about the latest enhancements to out-of-the-box document processing – with little to no training required Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath. Speakers: 👨‍🏫 Andras Palfi, Senior Product Manager, UiPath 👩‍🏫 Lenka Dulovicova, Product Program Manager, UiPath

UiPath Test Automation using UiPath Test Suite series, part 3

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To Graph or Not to Graph Knowledge Graph Architectures and LLMs

Paul Groth

FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf

FIDO Alliance

Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...

Thierry Lestable

Neuro-symbolic is not enough, we need neuro-*semantic*

Frank van Harmelen

Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”. All of this illustrated with link prediction over knowledge graphs, but the argument is general.

From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...

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Assuring Contact Center Experiences for Your Customers With ThousandEyes

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A study on the impact of data analytics in COVID-19 health care system

1. Sandya Jalesh [1] , Dr. C.V. Suresh Babu[2] [1] Student, Dept. of Information Technology, Hindustan University [2] Professor, Dept. of Information Technology, Hindustan University Abstract Through the disperse of novel coronavirus illness globally, existence became considerably contrived. Data analytics have experienced powerful development over the past few years. As it happens, it’s exceptionally considerable to take advantage of data analytics to assist mankind in a prompt as well as factually precise method to forestall additionally restrain the advancement of the widespread, sustain gregarious balance and evaluate the influence of the widespread. The unforeseen significant number of coronavirus disease instances has disturbed medical care system in many economies furthermore eventuated in an insufficiency of dormitory in the hospices. For this reason, prognosticating quantity of coronavirus infection instances is indispensable for administrations to adopt the necessary measures. The count of coronavirus disease instances could be correctly anticipated by taking into account historical records of announced instances side by side few extraneous components that impact the disseminate of the COVID-19 . Hence, the principal aim out of this research is to contemporaneously consider historical data and the extraneous components. This paper explores how data analytics can play a role in health care especially in novel coronavirus illness. Keywords: COVID-19, Data Analytics, Health Care system A Study on “The Impact of Data Analytics in COVID-19 Health Care System”

A study on the impact of data analytics in COVID-19 health care system

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