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Artificial intelligence in the health service has vast potential: from virtual assistance solutions to the discovery of drugs and the diagnosis of diseases. All features that fall within can be achieved with machine learning. The whole world, at this moment, is struggling to combat the Corona Virus. Around 1.5 million people from over 200 countries have been found affected by this disease. This disease is considered the most significant pandemic of this century if you look at the impact on the global level.
It is a virus that spreads from one person to another. Though medical practitioners from all across the world are trying their best to control and fight against it, the risk of doctors getting infected is irrepressible. We have already seen hundreds of doctors losing their lives due to the virus.
Thankfully, technology allows us to replace human resources with AI at most of the places, and healthcare is one of those. Sure enough, we need doctors, but we can utilize artificial intelligence for quite many tasks. This blog speaks about all those opportunities where AI can help fight the COVID-19 pandemic while controlling further damage.
In particular, healthcare will be increasingly permeated by assistants and robot doctors. In fact, according to Accenture, artificial intelligence applied to healthcare is a booming market that will produce a turnover of 6.6 billion dollars in 2021, with a jump compared to the 600 million dollars of 2014.
Artificial intelligence in healthcare refers to the use of complex algorithms designed to perform specific tasks in an automated way. When researchers, doctors, and scientists enter data into computers, algorithms can review, interpret, and even suggest solutions to complex medical problems.
To date, several health and pharmaceutical firms have used Artificial Intelligence to help the drug development process. Here's the triggering fact: 9 out of 10 prescription drugs fail to attain evaluations, and many more do not meet the approval process. It means increasing expenses funding the research and production of medicines.
The good news is that Artificial Intelligence, along with Machine Learning and Big Data, has tremendous potential to reduce the investment cost of new medicines.
Within clinical decision support, healthcare AI can be useful in helping clinicians make smarter, quicker decisions. Time saved and diagnosed illnesses are critical in an environment where time spent, and choices will save lives for patients. Artificial intelligence is not, given all these developments, the perfect cure for solving all healthcare problems. Like every breakthrough, it poses a variety of issues that need to be carefully discussed before full integration occurs.
Health care is, however, an environment full of obligations and regulations. Thriving technologies such as AI bear a significantly empty regulatory past with it. This could delay patient and professional acceptance because no one wants to risk a medical negligence case. We have already dealt with these issues by addressing the importance of ethics in artificial intelligence.
You can use artificial intelligence to identify different diseases and determine treatment plans. For example, a team led by scientists at the University of California and the University of Surrey, in Gilford, UK, announced an AI platform in March 2019 that can help identify and anticipate cancer development.
This a groundbreaking study shows how, along with machine learning, the team of scientists used network analysis to examine the interconnection that occurs between groups of 38 common symptoms, frequently documented by more than 1300 patients. For example, the AI-led platform allowed the scientists' team to recognize nausea as the key symptom, putting it at the center of their analysis.
The ability of artificial intelligence to adapt and "read" from medical data offers opportunities for researchers to study and forecast the Coronavirus on a whole new level. Through cross-referencing the data generated through research agencies, pharmaceutical companies, doctors, and practitioners with back-end databases, AI will help improve the accuracy of COVID-19 diagnosis and treatment.
Artificial intelligence in the medical field depends on the analysis and interpretation of vast amounts of data sets to support doctors:
Voice assistants are intelligent speakers equipped with microphones and connected in Wi-Fi, which, thanks to artificial intelligence and voice recognition, can execute orders given by users. In the health sector, they have two types of public: doctors and patients. Doctors often take notes, process data, and access patient records using programs. Data management, in controlling the time, is a vital aspect, and screen readers can be a viable solution.
From the patient's perspective, virtual assistants based on artificial intelligence can provide 24-hour assistance to a wide range of patients who might need access to care as a cheaper alternative to outpatient visits. Individuals who have chronic diseases, patients with disabilities with carers and patients living far from city centers are just a few of the people who could benefit most from virtual carers.
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Organizations around the world are struggling to engage with consumers through simple communications that are prevented by COVID-19 lockdowns. Most companies are using chatbots to solve these issues. Not only can these help them communicate with clients, but they also help spread knowledge of the current pandemic.
Chatbots have been a great help, particularly in this crucial period for healthcare, helping to spread knowledge about coronavirus and to help with customer queries. Below are some of the well-known chatbots that supported industry during the COVID-19 era:
Recently the World Health Organization (WHO), in partnership with Facebook, unveiled a chatbot to combat COVID-19. The new chatbot is now part of Messenger, the popular Facebook instant messaging app. By offering people immediate and accurate information about the virus outbreak through a chatbot, W.H.O. has extended its Health Alert network widely and effectively. After the virus pandemic, the demand for the production of the chatbot has exploded through industries and organizations.
The popularity of chatbots as a means of communication has dramatically increased, especially among the young generation. Chatbots are based on Artificial Intelligence (A.I.) conversational technology. They convey information to users through a text or voice-based interaction. Small and large organizations embrace chatbots because of their ease-of-use and efficiency.
The WHO's virtual chatbot, known as Rakuten Viber, aims to spread relevant COVID-19 outbreak information in several languages. The organization’s chatbot app production collaborates with Rakuten Viber. W.H.O. is aiming to reach more than 1 billion people worldwide with the chatbot.
The W.H.O. communicates in their languages with people in various countries and regions. The chatbot is currently available in English, Arabic, and Russian as of this writing. W.H.O. plans to extend the language capabilities of the chatbot up to 20 more languages.
The organization is assured that the messaging service will assist government officials, general citizens, and health workers stay informed about the pandemic. The information provides specifics for policymakers on signs, threats, security measures, and the current affairs reports.
Interactive chatbots have become the natural choice to spread health information amid the outbreak of the virus. For some time now, the software development industry has made considerable strides in natural language processing (N.L.P.). It resulted in the development of A.I. tools such as Siri, Alexa, and Google Assistant. Companies providing chatbot development services utilize conversational A.I. to create highly interactive chatbots. Those bots are deployed to disseminate knowledge about COVID-19.
Chatbots enables organizations to give people a low-friction, intuitive interface that makes it simple spreading information. More significantly, chatbots are successful all round the clock, which is critical in pandemic times. Chatbots also provide significant advantages in providing accurate information.
The information is often curated and dispersed through a chatbot. The details can also be personalized to match the target audience. For example, the United States Centers for Disease Control (C.D.C.) is using highly targeted information to raise American awareness of the virus.
Despite the fact that concerted efforts by governments and organizations around the world, Misinformation about coronavirus have spread widely over social media platforms. WhatsApp, the world's largest messaging platform, was working with W.H.O. to combat the deluge of Misinformation.
They were creating dedicated messaging services through WhatsApp. For the messaging program and answering COVID-19 questions, the website will also include alerts and the latest reports on the global pandemic. This collaborative chatbot app partnership is meant to play a significant role in combating fake news about COVID-19 cures, remedies, and risks.
The Indian Government has also adopted the Chatbot growth policy. It has launched a chatbot called a helpdesk MyGov Corona. The chatbot uses WhatsApp to provide checked information about the novel COVID-19-causing coronavirus. In the battle against the virus, even Indian states are not behind in deploying chatbot. For example, a chatbot named Cobot-19 has been launched by the Goa government. The bot was developed in collaboration with an automation start-up located in Bengaluru.
A chatbot is a software to simulate human communication through voice commands or text chats or both. Chatbots are tools based on Artificial Intelligence (A.I.), which can be integrated and used in any big messaging program.
A Chatbot 's creation cost depends on your needs and the intent of using the bot. The choice of platform for creation is also essential. When you need a simple chatbot embedded in an app, the cost would be comparatively smaller. More advanced, collaborative chatbots cost more than the simple ones.
Conversational A.I. is an advanced version of Artificial Intelligence that enables people to interact with apps, websites, and devices. It uses the techniques of natural language processing (N.L.P.). The chatbots are the most famous examples of AI-based conversational devices.
The COVID-19 pandemic contributed to the rapid expansion of the use of chatbot technology worldwide. However, that trend will stay here even after the end of the pandemic. The usage chatbots are expected to grow significantly as a platform for healthcare. To use chatbots as an essential tool for combating disease outbreaks and other public health problems, organizations need further partnerships.
We are dedicated to assisting businesses and organizations to combat the Battle of COVID-19. We deliver a range of digital solutions that help companies fight disruption. We firmly believe that together we will fight the unseen enemy with success.
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The whole world is anxiously grappling with the lockdowns and social distancing triggered by the COVID-19 epidemic. The virus outbreak is both an unprecedented challenge for the technology industry, and a unique opportunity too. Enthusiasts of artificial intelligence are pulling out everything to use this rapidly evolving technology as a tool to combat the pandemic.
Scientists, professionals and medical care experts worldwide are applying A.I. to understand better and contain the virus that causes COVID-19. This will allow them to treat infected patients better and potentially create vaccines that will avoid potential outbreaks.
For some time now, A.I. has played a tremendous role in enhancing the overall quality and performance of healthcare areas such as big data analytics and advanced computing. It has enabled the information to be shared and used in a completely new way. It has dramatically improved the awareness of diseases and illnesses by medical care practitioners. Given the severity of the global coronavirus epidemic, governments worldwide are using AI-based strategies to combat the pandemic.
Both medical researchers and virologists have pioneered work to understand the virus' structure. The epidemic has sparked unprecedented cooperation between researchers worldwide. It is primarily because of the COVID-19 outbreak size and severity. It is among the most contagious viruses ever known to the scientific community.
The virus structure represents a particular challenge for scientists. The virus belongs to an enveloped coronavirus family that comprises a single-started RNA structure. The fabric is covered up within a protein layer. It is similar to two-stranded viruses, such as HIV, Ebola, and Influenza. The tendency of the virus to mutate makes the production of a vaccine difficult for scientists.
That is where A.I. comes in. Tech companies around the globe are developing various AI-based techniques to assist the scientific community. Baidu Inc., for example, has made its Linearfold algorithm available to medical experts and researchers who are trying to control the pandemic. The Linearfold algorithm predicts the secondary RNA structure of the virus substantially more quickly.
The The AI-based algorithm offers useful insights for researchers on how the virus spreads from one species into another. Additionally, Baidu A.I. researchers have used the algorithm in predicting the secondary structure of the coronavirus. The phase of analysis was 120 times faster than the conventional way of analyzing the RNA.
Scientists believe that fast access to the virus's structure can shorten the development period for a vaccine dramatically with mRNA. Such vaccines may also have more excellent stability and effectiveness. Early vaccine development means a thousand lives are saved during an outbreak.
Together with machine learning, A.I. can effectively track the trends of the virus spread across communities, countries, and geographies. Better access to reliable distributed data can assist health care authorities in taking appropriate preventive and management steps. AI-based analytical methods can also be used to understand past patterns and trends in the spread. For healthcare practitioners, such observations will be incredibly useful. The authorities will establish successful containment strategies by integrating the AI-based data with the expertise of epidemiologists and other specialists.
Furthermore, A.I. and ML can be used to control infection risk. The most critical threats when it comes to coronavirus infection are habits and behaviors in humans. Such behavior patterns can be analyzed using A.I. and ML to manage risky behaviors and diffuse awareness.
Nearly every epidemiologist worldwide has emphasized the role of extensive screening and testing in containing the outbreak. South Korea was a premature adopter of this pattern. The country started widespread screening and managed to 'flatten the outbreak's curve without even imposing any lockdowns.
Healthcare authorities need to have active monitoring resources, especially in those places that are crowded like public places and hubs of transport. This would encourage healthcare professionals to isolate infected individuals and reduce COVID-19 spread. Tech companies and industries are developing AI-powered, infrared sensor systems that help humans in crowded places to monitor temperatures. China already uses these technologies in areas such as railway stations.
The novel coronavirus infection causes pneumonia as the most severe clinical disease. A chest C.T. scan is known for being the most accurate pneumonia diagnostic examination. With fewer medical care professionals in the middle of the outbreak, it has become challenging to conduct a large number of such diagnostic tests. The battle against COVID-19 will be more successful, with automated diagnostic tests and various medical care activities.
For example, LinkingMed, a company that analyzes medical data, has published an open-source A.I. model for the analysis of pneumonia C.T. images (source: MIT technology review). The AI-based technique can diagnose pneumonia rapidly and efficiently, and provide details such as the number, amount, and size of pneumonia lesions.
Also, automated medical care services such as telemedicine can be beneficial because of coronavirus infection for persons under quarantine or self-isolation. Such programs will improve the healthcare system and reduce the chance of contracting the virus for medical professionals.
The A.I. Avenue in the fight against COVID-19 is virtually limitless. A.I. and big data can be used together to explain the history of the spread of the virus across the globe. Methods of AI-powered data analysis will not only increase performance but would also help avoid future outbreaks.
We are observing the rapid developments in A.I. research and development. For AI-powered fast production of software and testing processes in place, we have the first-hand experience with A.I. technology. As a tech-driven company, we are hopeful that A.I. will drastically improve the fight against this invisible enemy.
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If you are using Microsoft Office, you have noticed several changes in the software suite application lately. Microsoft Word now offers better words or phrases; Outlook provides better support while writing an email; you get AI-based help when designing PowerPoint slides. Microsoft has ramped up the development of machine learning for its Office 365 applications. Both of these apps are machine learning based on Microsoft Azure.
Microsoft is continuously updating all those features and further expanding its machine learning capabilities. Also, the software recently renamed its most popular Office 365 suite to Microsoft 365. Microsoft is planning to give customers new apps and benefits. For instance, Microsoft 365 offers smart writing support in documents, emails, blogs, and many more. The Windows Editor-based AI and machine learning support have grown remarkably. Computer businesses are greatly benefiting from the partnership with Microsoft Office 365 and other similar initiatives.
Microsoft users have access to Microsoft Editor, which is an intelligent writing aid. This ML-based tool, among others, suggests better phrasing, grammatical errors, conciseness, and readability while typing. Such apps are more like writing aid tools such as Grammarly. Yet those are all built-in programs on Microsoft apps.
Azure machine-learning capabilities allow Microsoft to use a comparison of real-world numbers. The Bing browser has been using this for quite a while now. Combined with the advancement of machine learning, artificial intelligence implements such features as simple and more efficient. For instance, Word can recognize that the heading phrase is bold and recommend a style of heading.
The Outlook emailing software uses iOS machine learning to tell the user when to read an email. It can scan your message, as well. Also, Outlook applies machine learning and natural language processing (NLP) to recommend prompt answers to the emails you get. These replies may involve "looking ahead" or a schedule of meetings. Programming methods such as the development of Python enabled developers to incorporate these features efficiently into software applications.
For spreadsheets and any other significant document, Excel also uses NLP. It allows you to query your Excel data. PowerPoint Designer's machine learning capabilities can do great useful things for you. It leverages ML for text and slide structure analysis. The Presented Coach helps you to overcome issues such as slouching, speaking in a monotone, or even continually staring at the screen while presenting. With the use of machine learning techniques, the tool analyzes your voice and body posture.
Most of the machine learning skills that Microsoft applications offer are built using the Azure machine learning service. Features such as built-in Azure Cognitive Services APIs enable developers to create functionalities such as speech recognition. Many other features are focused on the creation of machine learning models, such as generating the Turing Neural Language. It is a model of profound language learning that has, among other things, the potential to learn to answer questions and full sentences.
The Azure Machine Learning platform enables both Microsoft and its partners to develop intelligent featured software solutions. It allows automation, processes data, and feeds the information into application training. These active machine learning and AI-based features facilitate collaboration with partners and Microsoft Office 365 to develop smart software solutions. We can expect more productivity-focused features in the future as Microsoft continues to upgrade its ML techniques.
Azure is a popular cloud computing platform with applications such as Service Infrastructure (IaaS), Service Application (PaaS), and Service Apps (SaaS). This is used for machine learning techniques and other applications, such as modeling, virtual computing, and networking.
Python is the most popular language of general-purpose programming used for the development of machine learning. R is used to analyze the data and to compute statistics. The machine learning language effectiveness depends on the region from which it is implemented.
Machine learning algorithms search for insight-generating natural patterns in the data. ML usage enables you to make better choices and predictions. They are used to create smart solutions every day, make important decisions in medical diagnosis and energy load forecasting.
Machine learning skills make your application software much more useful compared to the traditional solution. Microsoft enterprise software solutions are expertly designed to facilitate productivity for businesses and software developers. We use a wide array of Microsoft tools and technologies at our company to develop smart software applications.
Our customers are counting on us for feature-rich business solutions, which make business operations more efficient and profitable. Machine learning enables you to improve the productivity of businesses and allows you to understand your customers better. With increasing competition across different sectors, software solutions based on AI and ML will become the mainstream in the coming times.
15 Jun
2020
5
min read
