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Artificial Intelligence: The New Nervous System for the Healthcare Industry

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Artificial Intelligence: The New Nervous System for the Healthcare Industry

In healthcare, AI has seen a consistent rise in adoption. AI solves various problems for hospitals, patients, and the industry. Here are 5 ways AI is revolutionizing healthcare.

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The healthcare industry has been around for millennia. Although much has changed in the way it currently functions, it needs to transform into something better to serve the sick. To put it in simpler terms, the healthcare industry needs a new nervous system to function efficiently. This is where artificial intelligence comes into the picture.

In healthcare, artificial intelligence has seen a consistent rise in adoption. AI helps solve a variety of problems for hospitals, patients, and the industry, as well.

Here are five ways AI is revolutionizing the healthcare industry.

  1. AI chatbots: Chatbots, also known as intelligent personal assistants, are expected to take over healthcare messaging apps. These chatbots will ease the burden on medical professionals for simple health concerns and will quickly solve minor sicknesses.

  2. Apps: Medical apps help in interpreting and understanding lab test results.

  3. Emotional intelligence indicators: AI-based virtual assistants can pick up cues in speech and gestures to assess an individual's feelings and mood.

  4. Building prosthetic limbs: Using AI, building prosthetic limbs can be simplified. A few crucial mechanical parts can be replaced with AI to ease movement.

  5. Improving clinical documentation: Doctors and hospitals are using AI to document and bring-up old data.

In this blog, we will discuss how these five elements of AI are radicalizing the way the healthcare industry functions.

AI Chatbots

Healthcare providers usually shell out lots of money to employ customer service representatives (CSRs). The CSR's main role is to take patient enquires. This could be when patients walk into a hospital or clinic, or through telephonic conversations, or through email. This process is often cumbersome and leads to solecisms. Technology can help solve this problem with automated chatbots that are artificially intelligent.

Chatbots function using something called natural language processing. Using this, chatbots try to figure out what the individual is asking it. Once this is done, chatbots follow a certain flow for a particular sickness based on the symptoms that are provided by the individual. The data for a sickness and their related symptoms will be recalled from a central database that is constantly updated. Chatbots will also anticipate the next answer and can guide the individual to either a doctor, in severe cases, or advise medication. In addition to this, chatbots can also serve as knowledge management structures (KMS). KMS allows for documenting common Q&As that are accumulated over the chatbots lifetime. This feature helps in standardizing the service experience to patients. Chatbots will evolve over time, thanks to their machine learning techniques.

Apps

There are myriad mHealth apps available both for apple and android devices. However, most of these apps are targeted towards providing medical help, while only a few are targeted towards explaining lab test results.

Most patients have to undergo many tests during their time in the hospital. During their time there, nurses and doctors can easily explain the results. Some patients will have to constantly take medical tests after they are discharged from the hospital to make sure their sickness is in check and/or to make sure it does not resurface. Finding a doctor to explain the test results can be a task. To address this problem, many leading hospitals have developed apps that are gateways for information.

Using these apps, patients can connect directly with their doctors and understand if they need to change their diet, exercise more often, change their medication, and/or see a doctor immediately. Such apps also simplify scheduling tests, as well. There is a possibility to directly notify the concerned doctor if the tests of a patient are alarming.

Emotional Intelligence Indicators

The next big thing in artificial intelligence in the healthcare industry is emotional intelligence (EI). While conversational intelligence has penetrated our lives through virtual assistants like Siri, Cortana, and Alexa, similar technologies can help hospitals greatly. In the healthcare sphere itself, emotional intelligence structures are evolving rapidly. They are able to pick up cues from gestures and speech to make appropriate suggestions. Emotional intelligence is expected to provide a certain amount of ease in addressing patient emotional queries. For doctors, trying to understand a problem usually means that they have to look at their own experience or consult with their peers for a solution. With EI, doctors will have access to a plethora of information. With this, they can use their knowledge to better serve their patients.

While a few people feel that trusting a machine to make important decisions regarding their health and money, in the twenty-first century, this mindset will only cause more complications than solutions. Millennials, on the other hand, are embracing technology with open arms and they tend to trust machines over humans. Millennials know that machines are smart and usually portray the truth as it is, hence the trust. Furthering the point of trust, doctors are also learning to trust machines as they are able to crack medical cases that are often considered tough to doctors.

Building Prosthetic Limbs

Prosthetic limbs have not changed much over the last five decades. Prosthetic limbs of the future are expected to look and feel different than what we currently see. For example, bionic hands are expected to be fitted with miniature cameras that will help in recognizing the objects and assist in calculating the amount of grip needed to hold it. Responsiveness which was a hurdle that doctors or engineers could not address, can now easily be addressed using artificial intelligence. Individuals using the bionic arm just have to glance over the object they wish to pick up and the rest is done by artificial intelligence.

Artificial intelligence will make way for nimble prosthetic limbs over bulky ones. Although the technology is too complex to be implemented at the moment, it is expected to quickly iterate and ease the life of amputees across the world.

Improving Clinical Documentation

Since time immemorial, the healthcare industry has been documenting patient data. With the advancements in technology, five decades ago parts of this data were digitized. A few decades later, most of the data was digitized. With this digitization, doctors, clinicians, and medical representatives were able to access this data from anywhere in the world and at any time. However, this was the threshold of what could be done with the technology that was available then.

Now, with the advent of artificial intelligence, clinical records can be digitized and used to assist doctors. How is this possible? As AI is based on the natural learning process and deep learning, it can provide insights into a patient's health. AI can even alert clinicians or doctors if data regarding a patient is incomplete or inaccurate.

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With this level of efficiency in documentation, healthcare providers can easily assist patients while the insurance reimbursement process. As all the data is automatically brought up using artificial intelligence, the scope of something to go wrong is minimized. AI in clinical documentation helps in greater clinical efficiency at minimal prices. Obviously, the initial costs would be high, but once implemented, AI will take over traditional processes and in turn reduce costs for healthcare providers.

Conclusion

Artificial intelligence in healthcare is necessary to take the industry to the next level. Other industries such as hospitality, education, gaming, etc. have already implemented artificial intelligence and are witnessing great success. Similarly, the healthcare industry needs to implement artificial intelligence at the earliest to experience analogous results.

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Topics:
ai ,healthcare ,chatbots ,machine learning

Published at DZone with permission of Robby Gupta, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

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