How AI Is Used in Healthcare: Technologies and Benefits

People may not yet cooperate with human-like robots every day. However, technological progress is already here, with Siri, Alexa, GPT chat, and smart home appliances. As we can see in the latest statistics, the AI market will continue to grow in the future, reaching over 1.8 trillion US dollars by 2030, compared to 200 billion in 2023.

AI technologies are visible in every aspect of life, so the healthcare industry is no exception. The effectiveness of medical services depends on precise data analysis, speed of interaction, and information security. In this post, the experts from the Belitsoft Software Development Company outline the range of AI technologies and their current uses. 

Types of AI Technologies

Before plunging into what AI in healthcare is, it is good to review the basics. Generally speaking, AI encompasses the following types of technologies:

• Machine learning is the central technology behind AI. The system researches thousands of materials, web pages, documents, images, etc., and learns to use that data to draw conclusions and analyze the information. In the medical field, this functionality can make disease diagnoses, suggest treatment, and detect changes in health conditions based on various tests.
• Natural language processing (NLP) is a system that can understand and use human language for direct interactions between people and computers. This technology streamlines administrative processes and improves diagnosis procedures. For example, AI can not only digitize a patient’s record but also compare it with similar cases and send it to a relevant specialist if any information is missed or looks suspicious. As a result, AI technology participates in data validation and decision-making processes.
• Computer vision can read scans and pictures. Medical experts use this technology for fast MRI or X-ray analysis. A program examines images and can detect deviations from the norm. Such a technology aids, for instance, in finding skin anomalies, tumors, fractures, etc.
• Robots add superpowers to people in various fields. For example, they can help to perform heavy lifting or assembling tasks at a construction site or warehouse. In medicine, the robot abilities are used for moving bedridden patients or assisting surgeons. Robots improve doctors’ vision, and aid in suturing and precise surgical interventions.
• Rule-based expert systems: “if-then” rules are at the core of similar solutions. Medical experts utilize those algorithms mainly in Electronic Health Record (EHR) systems. All the data about patients’ tests, diagnoses, treatment, and medications are stored in a repository, enabling any medical provider to examine the information and make a well-grounded decision regarding each case.

AI applications in healthcare

AI in healthcare data analysis

While robotic assistants are still more of an idea of the future, AI has upheld its position in healthcare data analysis. Dozens of modern devices can gather information about a patient’s health condition. Smartphones, watches, biosensors, smart scales, and other gadgets compile the evidence for medical history and make it easier for doctors or nurses to collaborate. Additionally, AI features in modern devices allow for notifying patients of the necessity to take a pill, have some physical activity, or take a break from the screen. The treatment process takes less time if a patient carefully follows all the recommendations, so AI becomes a valuable assistant.

Automatic speech recognition technology is another tool for simplifying hospital routines. The possibility of converting speech into written text speeds up the process of gathering symptoms and noting down other medical information. Algorithms analyze this data, provide similar medical cases, warn of possible risks, and advise on therapy plans. Advanced AI features include data extraction and transformation. It is like consulting a virtual library that knows exactly what you are looking for and can come up with a summary of the relevant cases. 

AI in medical diagnosis and treatment

People started experimenting with artificial intelligence in medical diagnosis at the end of the 20th century. Though the results appeared quite promising, the system was too complicated for everyday use. That is why it was not adopted for clinical purposes.

With the development of AI, systems learned to evaluate, for instance, radiological pictures and retinal scans. Although nowadays, doctors still cannot entirely rely on AI, it works well as an additional supportive tool. For example, the AI implementation is utilized in X-rays, MRIs, and CT scan interpretation. Besides, AI can perform drug tests. Virtual assistants can make a diagnosis and suggest appropriate treatment. Human doctors take those suggestions into consideration while making a final decision. In the sphere of nursing care, chatbots and virtual health assistants support patients and allow strict adherence to the recommended treatment plans.

AI in medical administration

Medical staff have to spend large amounts of time on paperwork. AI can improve the situation and release medical professionals from those tiresome duties. Automated programs can fill in patient information forms, operative reports, tests, examinations, and discharge summaries. Further handling of those documents involves storage, sharing, and accessibility. Chatbots can take on the responsibility of performing routine tasks like gathering simple anamnesis and making appointments. Telemedicine, which gained popularity during and after the lockdown also gives credit to AI functionality with automated requests and virtual consultations.

Machine learning and optical character recognition technology simplify billing and scheduling, allowing for efficient documentation. AI can check the insurance information and execute a general claims audit to avoid financial losses. Automation reduces the risks of human attention distraction.

Conclusion

Artificial intelligence strengthens the functionality of medical providers significantly. Doctors and other medical professionals use AI for quick analysis of tests and medical images. AI can recognize the data and provide an analysis of the symptoms. Besides that, AI assists with administrative tasks, such as scheduling appointments and collecting patient information. Implementing AI into a medical document management system allows for the safe sharing of data and easy access to a patient's history from a different medical provider. All those possibilities facilitate routine medical staff activities and allow doctors to concentrate on treatment as the most crucial part of their profession.

About The Author: Dmitry Baraishuk is a partner and Chief Innovation Officer at the software development company Belitsoft (a Noventiq company) with 19+ years of expertise in digital healthcare, custom e-learning software development, and Business Intelligence (BI) implementation.