Artificial intelligence (AI) comes as the simulation of human intelligence in machines. These think-like-human programs label and analyze data to make predictions about future states. AI has over-grown over the last few decades and is gradually making its way into almost every industry. Healthcare is no exception.
In this article, we’ll walk your way up to the potential of AI in healthcare and bring to the table its benefits. We will also look at some of the most common types of AI technologies used in healthcare and their individual use cases.
Without further ado, let’s get started!
What is AI in Healthcare?
AI in healthcare is the use of computer systems to perform tasks that would otherwise require human intelligence, such as pattern recognition and decision making. In other words, it’s all about using machines to automate and improve various processes within the healthcare industry.
Artificial intelligence allows healthcare organizations to analyze a vast amount of data, including images, clinical research, and medical claims. As a result, you can have patterns and insights into complex biological datasets.
Types of AI Technologies in Healthcare
There are a plethora of types of AI technologies in healthcare, including:
Machine Learning: Enables computer systems to learn and improve from experience without being explicitly programmed. In healthcare, machine learning algorithms perform image recognition, predictive analytics, and fraud detection tasks.
Natural Language Processing (NLP): Let computer systems understand and interpret human language. The healthcare industry makes use of NLP for clinical documentation, patient monitoring, and medication adherence projects.
AI is supporting multiple areas and stakeholders in healthcare and medicine.
Predictive Analytics: Predict future outcomes based on data from the past and present. For instance, predictive analytics can be used to predict the likelihood of a patient who is developing a certain disease.
Personalized Medicine: Develop treatment plans that are tailored to individual patients. This is made possible by considering a patient’s genetic makeup, lifestyle, and other health-related factors.
Disease Diagnosis: Use AI to diagnose a disease based on symptoms, medical images, and lab tests. Take kidney disease as an example. Detecting acute kidney injury (AKI) is not always an easy task. Patients will quickly suffer life-threatening due to late prediction and treatment. By making use of AI tools, we can reduce the AKI prediction time by 48 hours compared to traditional methods.
Drug Development: Use AI to speed up the process of drug development by identifying potential targets and predicting how a new drug will interact with the human body. Based on existing biological datasets, you can examine the new uses for current medicines instead of investigating and creating new ones which are less expensive.
Patient Monitoring: AI assists in monitoring a patient’s health in real-time and identifying potential health risks. Natural Language Processing and Machine Learning can read their medical history, analyze symptoms, and connect with chronic affections.
On top of that, real-time analytics also tighten the relationship between physicians and patients. Mobile alerts will quickly inform doctors and nurses of the urgent status of patients’ illnesses.
Benefits of Artificial Intelligence in Healthcare
The contributions of artificial intelligence in healthcare are undeniable. Not only does it deliver more accurate patient outcomes, but healthcare organizations can also develop medicine at less expense.
Several potential benefits can motivate you to apply artificial intelligence in healthcare. Some of the most notable ones are:
Improved patient outcomes: By automating various processes within the healthcare industry, AI dramatically improves patient outcomes. For instance, it can help doctors make better decisions by providing them with more accurate and up-to-date information.
Reduced costs: One of the main goals of AI in healthcare is to reduce costs. For instance, hospitals are able to make more efficient use of their resources and staff. In addition, AI-enabled automation can speed up processes and reduce the need for manual labor.
Imagine you have to check and analyze vast amounts of data and images for a clinical study. This process requires the involvement of numerous people to read and identify the result, while AI tools can process it in seconds.
Improved access to care: AI proves advantageous in healthcare by improving access to care. By way of example, AI-enabled chatbots can provide patients with 24/7 access to a medical professional. In addition, AI can also be used to improve the efficiency of the whole healthcare industry, making it easier for patients to get the care they need.
Are There Any Limitations of AI in Healthcare and Medicine?
Besides significant advantages, there are still some risks associated with the use of AI in healthcare.
There are chances that your patient data is mishandled or misinterpreted. We need human surveillance to diagnose or prevent medical complications in various circumstances. On the other hand, surgery robots, for example, follow logic only.
AI-enabled automation can also lead to job losses in the healthcare industry. It’s majorly because artificial intelligence is can more integrated across different sectors, handling jobs of multiple people in various sectors. A 2018 World Economic Forum report estimated that AL would make 75 million people unemployed that same year.
Plus, a lack of regulation surrounding the use of AI in healthcare is a significant concern. Currently, no specific laws or regulations govern the use of AI in healthcare. Consequently, there is a risk that AI may be used inappropriately or even maliciously.
To mitigate these risks, ensure that AI is used responsibly and ethically in healthcare. This can be done by setting up clear guidelines and regulations for the use of AI in healthcare.
The Future of AI Technologies in Healthcare
AI has an enormous potential to transform the healthcare industry. We can use it to improve patient outcomes, reduce costs, and improve access to care.
However, some risks are also associated with using AI in hospital and medicine. These risks can be mitigated by setting up clear guidelines and regulations. With proper implementation, AI can transform the healthcare industry for the better.
I'm Trinh Nguyen, a passionate content writer at Neurond, a leading AI company in Vietnam. Fueled by a love of storytelling and technology, I craft engaging articles that demystify the world of AI and Data. With a keen eye for detail and a knack for SEO, I ensure my content is both informative and discoverable. When I'm not immersed in the latest AI trends, you can find me exploring new hobbies or binge-watching sci-fi
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