Artificial Intelligence (AI) and other related innovative technologies are just at the beginning of their application in healthcare. Recent studies have shown that if artificial intelligence applied right it can serve better than a human in healthcare. Many healthcare tasks will be executed better with AI such as diagnosing diseases. The best guess is that there could be years before AI replaces humans for medical processes. In this article, we will review the latest AI development in healthcare and what’s the market’s response.
Artificial intelligence has many different technological types and most of these devices find immediate influence in the healthcare field of work. On the other hand, AI is still not capable to handle specific and complex processes. To illustrate some of them we know we will preview some of the most interesting types.
Conversational Language Processing
That would be the main goal of artificial intelligence since the 1950s. AI language processing is a Natural Language Processing (NLP) application included in many technological devices with text analysis, recognition, translation, and more.
The natural applications of NLP in healthcare include the classification, creation, and understanding of clinical research documentation. Natural language processing is capable of analyzing structured data and clinical notes on complex patient reports. This way they can receive complicated data and output it with conversation AI.
Rule Expert Systems
Rule Expert Systems are a collection of “If-then” programming functions that were dominating the technology of artificial intelligence back in the 1980s. Devices like this were adopted by the healthcare industry most commonly for “clinical decision support”. Nowadays there are still many Electronic Health Records (EHR) providers assisting in healthcare with their rule execution capabilities.
Machine Learning AI
In machine learning, there is a statistical technique that fits models into the data by “learning”. It is one of the most common types of AI and in healthcare, the most common application is learning treatment contexts and protocols. The circumstances in each project are unpredictable and trying to learn data that has a solution in each possible outcome is hard, but not impossible. Machine learning AI already has proven its capabilities in the healthcare field of work and market and it is already an active aspect in many projects.
More than 200,000 industrial robotic systems are installed around the world each year. Robots can perform and complete pre-designed daily tasks including repositioning, assembling, and welding. Robots became collaborative with humans and their application in healthcare is in operations requiring extreme precision. For example, this innovative technology is used in surgical procedures such as prostate surgery, gynecologic surgery, neck, and head surgery.
Speaking of healthcare, the majority will probably never completely trust the technology for such a complex and important data input with customers. The healthcare chatbots are using AI, for example, the 2020 COVID-19 has stimulated many AI developers to introduce an input-based chatbots gathering data from potential COVID patients. However, this input has proven significant results in mass collecting data but the accuracy will never be good enough in order for this technology to be the main data collection aspect in a pandemic.
All this tells us that AI chatbots and AI overall position is in a purgatory state in which any innovation may be the key for complete implementation on the customer market and complex healthcare.
Customer’s trust is not an easy thing to earn, especially for healthcare companies that introduce AI in their treatment. People are still not confident enough and prefer old methods. Another point of view is that the customers are guarded when it comes to their personal health details and data, just like the personal info. This is great but the majority is still concerned to share personal info on the internet. Looking through this scope, AI chat robots are online and even if they are trustworthy to secure the data, the customer’s trust is still an issue.
Many industries recorded an increased level of online orders and a decrease in their physical facility sales. With voice, assistance will be possible to buy daily consumables from the nearest grocery store by just calling to a voice assistant that will initiate delivery to your door. The important aspect is to handle the customers quickly, safely, and efficiently. For the first time, we have such an advantage thanks to the voice assistant, which provides us with the ability to adapt in pandemic times and take safety measures.
Healthcare applications have great potential but still a long way to go in order to earn the customer’s trust. The idea of reducing or completely removing the need for physical contact was re-born in the healthcare industry with the 2020 pandemic but even in times like this, it was not implemented entirely. When healthcare finally adopts AI it will change the way we receive our treatment and medicine prescriptions. The interesting fact is that according to Juniper Research the chatbots estimated cost savings is annually $3.8 billion in the healthcare field of work.
Another curious fact would be Google’s Deepening Health. Located in London, England Google’s DeepMind Health AI software is commonly used in many hospitals over the world in order to help patients for more efficient treatment and tests. The DeepMind technology is capable of combining, comparing, and analyzing symptoms in order to conclude significantly accurate diagnostics, but the human touch is always mandatory.
Our best guess would be that AI is an important aspect and it plays a vital role in healthcare with his offerings in the future. Early efforts for implementation of AI in healthcare have proven significant benefits over the industry, considering that an extremely precision device can perfectly fit field of work that requires it. Driven by the great advances that AI is providing the healthcare industry including analysis, automatization, and speech the implementation has already started and great future innovations are expected.
The greatest challenge, however, that AI healthcare specialists are facing is the concern if the technology is capable enough and trustworthy to be allowed to decide life-saving matters. If we have to look into the future, these concerts could be overcome and AI will become important and beneficial in my healthcare activities.
You would like to find out more about the possibilities of AI and voice assistants in healthcare? Here is the link.