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AI trends in Healthcare 2021 - Evolvous

AI trends in 2024

Artificial intelligence (AI) and its subdomain Machine Learning (ML) have been showing promising trends over the past few years. On one side, AI is transforming the way of living and human interactions almost in every industry on a large scale. On the other side, the restrictions and policies imposed during the COVID-19 pandemic have turned out to be an advantage for AI to grow. Given the lockdown situation and businesses turning towards digital transformation, AI has emerged as an only futuristic technology that is not only solving and automating manual business workflows but also helping in reducing the cost. The year 2021 has witnessed many unique platforms, research and tools that utilize AI to great extent, but the year 2024 has promised much more.

Robotic Process Automation (RPA)

It’s one of the most disruptive AI technologies that help in performing repetitive manual tasks. It can efficiently perform a high-volume, repetitive task on the desktop without creating any mess. Robotic Process Automation is a robot that works on using software for performing repetitive manual tasks. If there is something beyond the knowledge of the robot, it notifies its owner in a nutshell. RPA performs mundane tasks and gives time to your staff for more important work.

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RPA would be used in billing, invoicing, payroll processing, extracting data, tracking, and shipment scheduling. It is also known as Hybrid Workforce – a collaboration of the human workforce with robots. The combination of humans and technology helps in providing better services to clients. However, the RPA system cannot eliminate the need for humans.

AI Trends in Healthcare

AI is already helping the healthcare industry to a great extent with high accuracy, but further advancements will surprise everyone. AI developing companies are struggling hard to create advanced tools for enhancing the health industry’s capabilities. Big Data was used to identify COVID Patients and significant hot spots. Moreover, researchers developed thermal cameras and smartphone apps for measuring the temperature of individuals and collecting data for healthcare organizations.

AI can help the healthcare department in many unique ways by using data analysis and predicting different results. AI and ML tools provide insights into human health and also suggest preventive measures to stop the disease from spreading. AI Watches can help doctors to track their patient’s health remotely.

Why need Health Assistants?

Health Assistants are trained to provide basic health care, though their duties can vary greatly depending on their employer. As a Health Assistant, you are able to offer services such as wound dressing, administering oral medications, and equipment maintenance. You may be called upon to perform life saving measures in the event of an emergency. AI Trend in Healthcare.

Predicting Pandemic Even Before It’s Start

Now researchers are working on advanced AI algorithms for accurately predicting future outbreaks. Some of the significant research is already done on it that generated some earliest alerts about the current pandemic. In Wuhan, China, the Blue Dot Tool by a Toronto based start-up was scanning over 100,000 governmental and media data daily and shared an alert about the potential pandemic.

AI for Cybersecurity & Data Breaches

The use of advanced AI tools is to collect and analyze a wide range of data sets. It fetches information from news, blogs, websites, and stories to identify all threats. In 2024 and beyond, digital data will be at more risk to be hacked and vulnerable to phishing attacks. AI and advanced technologies will provide support to the security department against malicious activities in every field. AI will help to prevent cybercrimes in future with enhanced enterprise cybersecurity measures. The AI-supported system will spot fake digital activity or transactions that follow criminal patterns.

Its preventive alarms will protect sensitive data information from data hacking firms. Furthermore, it will take only a few seconds to detect any threatening activity, including suspicious IP addresses. It allows security dealers to respond to these activities faster than usual. Because of its high efficiency and advantages, the demand for AI in cybersecurity will rise in 2024.

Natural Language Processing (NLP)

Here machine learning models teach computers to understand what’s written or spoken material describing a specific process. It becomes one of the top and highly demanded applications of AI in the present time. NLP eliminated the need for writing or interacting with a screen as now humans interact with robots that understand their language.

Natural Language Processing comes with two sub-applications.

  1. Natural Language Understanding: As its name shows, it enables a machine to review a written text and understands its meaning correctly.
  2. Natural Language Generation: It’s a logical response that a machine generates for any given input, for instance, any text.

The use of NLP will increase in 2024 for sentiment analysis, machine translation, summarizing a process, auto-video caption generation and chatbots. YouTube uses NLP technology in generating captions automatically across its platform. YouTube Video involves a speech recognition software that produces video cations. The system used this technology first in 2009 for the translation of dozens of languages.

Reinforcement Learning

Reinforced Learning (RL) is one of the demanded skills of the future by different organizations. It’s a particular application of deep learning that works based on its experience for improving data’s effectiveness. In this learning process, the software is ingested with several different conditions that tell about its specific task performance. Thus, various actions define about self-learned actions of software that it performs to get the final result.

For instance, Chatbot has information to respond to a general user’s queries like greetings, order booking, or consultation calls. Machine Learning Development Companies can add sequential conditions in chatbots by using RL. It will make them more productive and helpful in getting more sales and transferring calls to the relevant department. Some other useful applications of RL are robotics in planning business strategies, advertising content optimization, automating industries, controlling aircraft, and making motion control robots. Moreover, it allows personalized recommendations with the optimization of the product’s advertising budget.

Alibaba, an outstanding Chinese e-commerce site, uses Reinforced Learning to boost its return by 24% for online advertisement without rising its budget. The team at Alibaba explained in a research paper that how they used RL in optimizing sponsored search campaigns. They created a bidding model for impression every hour and performed real-time bidding with it.

2022 has a lot in store, it can be rightly said that this year is the golden year for AI implementation. One needs to keep a close watch on the AI trends and wait to watch the rising trends.

Conclusion: In this article, we have explored the ways that AI trends in healthcare industry and provided some predictions for where AI is headed in healthcare. We hope you found this article helpful! If you would like to learn more about how we can help your business use AI successfully, please contact us today.

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