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COVID-19: What Can Artificial Intelligence Contribute to Healthcare Industry

COVID19 What Can Artificial Intelligence Contribute to Healthcare Industry

 

One can hardly escape the mention of Artificial Intelligence, or AI for short, today. AI is reshaping economies, promising to generate productivity gains, improve efficiency and lower costs. We see AI in the movies, books, news, human vs computer games and online. AI is part of robots, self-driving cars, drones, medical systems, online shopping sites, and all sorts of other technologies that affects our daily life in so many ways. It contributes to better lives and helps people make better predictions and more informed decisions. AI is also altering the professional world and this also affects the IT specialists themselves, as their routine activities, sometimes even programming, are beingcarried out by algorithms.

 

AI technologies are seeing rapid acceptance in multiple sectors, such as, healthcare, criminal justice, transport, agriculture, finance, marketing and advertising, science, security the public sector, as well as in augmented and virtual reality (AR & VR) applications. As AI systems can detect patterns in enormous volumes of data and model complex, interdependent systems to generate outcomes that improve the efficiency of decision making, save costs and enable better resource allocation, it’s gaining greater public awareness during the corona pandemic.

 

A Canadian company’s advanced artificial intelligence system Toronto-based BlueDot, was among the first in the world to notice the coronavirus disease emerging from China, by using AI-driven algorithm to go through more than 100,000 articles every day in 65 languages looking for news about more than 150 different diseases. Around 10 a.m. EST on Dec. 31, their system spotted an article in Chinese about a “pneumonia of unknown cause” with 27 cases.

 

The corona crisis confirmed to be a motor for the further development of artificial intelligence. The idea of creating an artificial machine is as old as the invention of the computer. Alan Turing in the early 1950s proposed the Turing test, designed to assess whether a machine could be defined as intelligent. Learning algorithms have long since found their way into everyday life – in the form of navigation systems, voice assistants or vacuum robots.

 

Today AI technologies are playing a huge role to fight back and limit the damages caused by COVID-19 outbreak by detecting and diagnosing the virus and predicting its evolution. Once the virus is studied in detail, it’s medical research on drugs and treatments can be accelerated. Further than that, AI technologies and tools are playing a key role in detecting and diagnosing the virus and predicting its evolution and understanding it in every aspect to accelerate medical research on drugs and treatments. AI is already being used for a range of healthcare and research purposes, including detection of disease, management of chronic conditions, delivery of health services, and drug discovery. Artificial intelligence has the potential to transform how care is delivered and to help address important health challenges, without the right data it has its limits.

 

When talking about AI, many people still think of process optimization, such as replace many routine processes, repetitive tasks that are tiring for people. However, AI can do much more than that, through machine learning, the generation of knowledge from experience, the algorithms are able to deal with unknown data, find patterns and independently derive actions. Chatbots, for example, which are increasingly used in customer service, are getting better and better over time as a result of supported learning. Deep learning based on neural networks enables predictions based on very complex relationships. In order to recognize and use the full potential of AI, IT users not only need development and implementation services, but also comprehensive advice. Because the use of AI elements is not comparable to the introduction of new software. As consulting skills, knowledge of AI systems and industry knowledge are becoming more important, IT consultants and business analysts need to have a knowledge background in order to familiarize potential users with the possibilities of artificial intelligence.

 

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Machine Learning: An Artificial Intelligence approach

I’ve heard a lot of people saying that Machine Learning is nothing else than a synonymous of Artificial Intelligence but that’s not true at all. The reality is that Machine Learning is just one approach to AI (in fact it’s called the statistic approach).

 

Let me first give a definition of Machine Learning. It’s a type of artificial intelligence that gives computers the ability to learn to do stuff via different algorithms. On the other hand Artificial Intelligence is used to develop computer programs that perform tasks that are normally performed by human by giving machines (robots) the ability to seem like they have human intelligence.

 

If you are wondering what it means for a machine to be intelligent, it’s clear that “learning” is the KEY issue. Stuffing a lot of knowledge into a machine is simply not enough to make it intelligent. So before going far in the article, you must know that in the field of Artificial Intelligence, there are 2 main approaches about how to program a machine so it can perform human tasks. We’ve a Statistical Approach (also known as probabilistic) and Deterministic Approach. None of these two approach are superior to the other, they are just used in different cases.

 

The Machine Learning (=Statistic AI) is based on, yes you’ve guessed right, statistics. It’s a process where the AI system gather, organize, analyze and interpret numerical information from data. More and more industries are applying AL to process improvement in the design and manufacture of their products.

 

There’ll be around 5 to 20 billion connected devices within 3 years and so many capture points will be used to make live decisions, to recommend, provide real-time information and detect weak signals or plan of predictive maintenance. Whether it’s at the level of business uses, the sectors of industry and services (health, distribution, automotive, public sector …) or even the use of Business Intelligence, everything is changing! With the Machine Learning and voice recognition technology based on AI, even the Big Data technology might be quickly overtaken by real-time information.

 

In a preview of an upcoming e-book, “AI & Machine Learning”, UMANIS talks about The Data, machinery and men. In the e-book they have elaborated problems and expectations that different companies are facing in the technological era.

 

Based on the responses of 58 participants who responded to the survey “AI & Machine Learning”, here below you’ll find identified trends and indicators.

 

  • 44% of companies believes that AI and Machine Learning have become essential and latest trend in various fields including education, healthcare, the environment and business sector,
  • One company on two is curious about the technological innovations in order to understand the collection of data (via machine)
  • 1/3 of companies are currently on standby on AL & Machine Learning topics,
  • 21% of IT decision makers were informed about Cortana suites (Microsoft) and Watson (IBM)
  • 36% want to go further on this type of technology,
  • 88% are planning to launch an AL project within more than 6 months,
  • 50% of respondents are unaware of the purpose of these technologies in the company.

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TOP 5 issues:

  • Detect abnormalities
  • Using machine learning to optimize the automation
  • Integrating a Learning Machine module into an existing SI
  • Remodeling of the real-time Data architecture to gather big volumes with high computing power
  • Finding a permanent solution of storage and backup of the collected data

 

There’s no doubt that machine learning area is booming. It can be applied to high volumes of data to obtain a more detailed understanding of the implementation process and to improve decision making in manufacturing, retail, healthcare, life sciences, tourism, hospitality, financial services and energy. The machine learning systems can make precise result predictions based on data from training or past experiences. By gathering relevant information for making more accurate decisions, machine learning systems can help manufacturers improve their operations and competitiveness.

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