Future of Health: Artificial Intelligence Technologies in Health Sector
Future of Health: Artificial Intelligence Technologies in Health Sector
Artificial intelligence and connected technologies continue to transform our daily lives and the world as we know it. While these technological developments are taking place in different fields and sectors, perhaps the most important of these sectors is the health sector.
This article answers questions like:
- Which AI solutions are being used effectively in healthcare?
- In which branches of health are these solutions specifically used?
- Will artificial intelligence technologies replace doctors?
Types of Artificial Intelligence Technologies Used in Healthcare
When we talk about artificial intelligence technologies, we may have different images in our minds. Some of us may perceive AI as a highly intelligent and human-like robot, while others may think of an advanced computer.
In fact, AI technologies are a collection of many different technologies, algorithms, and solutions. In the healthcare sector, these different technologies can be used to serve different purposes. Let's examine which of the AI technologies, algorithms, and solutions have initiated change in the healthcare sector.
Machine Learning and Deep Learning
Machine learning is one of the most widely used types of artificial intelligence technologies. Machine learning algorithms are the training and self-learning of algorithms using data sets. Although it is the simplest term for technology, machine learning is a very revolutionary technology and is the first technology that most organizations have adopted among artificial intelligence technologies.
One of the most common uses of machine learning in healthcare is based on the use of statistical data.
With the supervised learning model, data on diseases and their treatments, patients for whom treatments have been used before, and results are presented to the algorithm. Once the algorithm has learned these, it makes predictions and recommendations for future patients and treatments. In other words, it contributes directly to the treatment process as a consultant or decision-maker.
You can learn more about machine learning by checking the following articles
· How Do Machines Learn? : Understanding Machine Learning
· Top 5 Interesting Machine Learning Stats in 2022
· Machine Learning in Business Life (2022 Use Case)
Natural Language Processing
Natural Language Processing, or NLP, is the technology that enables machines to make sense of human languages. In this way, functions such as speech recognition, text analysis, text generation, or translation can be carried out by computers.
In the medical field, NLP can be used in many different ways. It can analyze doctors' notes in bulk, find specific symptoms and diseases in bulk texts, or perform text analysis by scanning medical journals.
In the future, it is planned to improve the voice recognition functions of these technologies. For example, predictions about the diagnosis of the disease and recommendations for treatment from the patient's voice analysis are among the things expected from the algorithms. Looking at the current situation, it is possible to say that development is not far away.
Robots have been around for a long time. From small household appliances to robots in factories, they are actively used in production and consumption.
Industrial robots are actively involved in the production line in different industries. These robots, which have specific functions, have replaced people in areas such as lifting things or doing repetitive work.
The situation is no different in the medical field. Physical robots can perform some tasks that are very difficult for doctors. It is possible to say that these robots are used especially for surgical purposes. They can provide images to doctors with their cameras or undertake delicate operations such as cutting or sewing. These robots are frequently used in surgeries such as gynecology and prostate.
Robotic Process Automation
Robotic Process Automation, or RPA for short, refers to the undertaking of office tasks by robots. These robots are not physical robots, but computer software. Compared to the other technologies mentioned above, they are more affordable and easy to use.
Thanks to RPA, tasks such as data entry, accounting, record keeping or record updating, and invoicing are done by artificial intelligence. Taking over these tedious and repetitive tasks with this software reduces the margin of error and speeds up business processes.
RPA technologies are gradually developing and integrating into other systems. For example, they can gain new features such as visual processing. Thus, they can also make sense of visual data.
Clinical Areas Where Artificial Intelligence Technologies Are Used
Medicine consists of many different specialties. The requirements of each of these specialties are different from the others. Artificial intelligence technologies are used more effectively in some clinical areas than others. In this part of our article, we will take a look at the clinical areas where artificial intelligence technologies are used.
In the list below, you can find medical fields that frequently benefit from AI technologies. Brief information about these fields is also included in this section.
- Infectious Diseases
We will take a look at some of these areas and examine the functions of artificial intelligence technologies in clinical areas.
Great progress has been made in the field of dermatology thanks to image processing and computer vision technologies. For example, while the correct detection rate of skin cancers with the human eye is around eighty-six percent, the accuracy rate has increased to 95 percent with artificial intelligence technologies.
In the field of heart disease, there are some algorithms that can analyze the risk of heart disease and recommend treatment based on patient records and data on their current condition. Smartwatches and other wearable technology products also collect important data by providing pulse monitors.
Again, the data learning of artificial intelligence and machine learning-based technologies has become prominent in this field. Algorithms that learn from previous data are more successful in discovering cancer in patients. Although there is not a huge percentage difference, it would be appropriate to say that this is a very important development in health.
Although many of the algorithms developed in the field of psychiatry are developed by private companies, it is necessary to be hopeful about the future of technologies in the field.
Algorithms can also be used in the field of psychiatry for symptom and diagnosis matching or drug and treatment recommendations.
We first used AI support for diseases caused by viruses during the COVID-19 pandemic. Features such as corona detection in lung films made the work of doctors much easier with artificial intelligence. During this period, especially the USA came first with serious investments in this field.
On the other hand, AI-based algorithms can also detect diseases such as malaria, and hepatitis B or C with blood tests and antigen or antibody counts.
Artificial Intelligence Impacts in Various Examples
We have talked about different examples of AI technologies used in healthcare and the clinical areas where AI technologies are used. In this part of our article, we will take a look at other examples of how AI technologies are impacting the healthcare sector. You can find descriptions of these examples in the list below.
Electronic Healthcare Records
It would not be wrong to say that electronic patient records were the first step in the digitalization of the health sector. Now, these records are being automated. In this way, it is possible to reduce the responsibility of record keeping and prevent incorrect entries. It is also a big plus that the records processed by artificial intelligence will be used for different analyzes in the future.
Developed Pathology Images
For pathologists, it is important to be able to visualize the site of the disease in order to make the correct diagnosis. Thanks to artificial intelligence technologies, the quality of these images can be improved.
Developed Radiology Tools
MRI, X-rays, or CT scans do not provide very clear images or data. Although they are very important and life-saving technologies, having more advanced radiology technologies in these areas will lead to great advances, especially in the diagnosis of diseases.
Thanks to artificial intelligence technologies, an improvement in radiology technologies are also expected.
Advanced Immunotherapy for Cancer
Immunotherapy is a type of cancer treatment that uses patients' own immune systems to attack cancer cells. Although the treatment is promising, the number of patients responding to it is currently very low.
Doctors believe that machine learning algorithms that will be trained in this field can offer specific treatment recommendations to patients by learning and comparing them with large data sets.
For patients taking more than one medication at the same time, drug interactions are a major risk factor. Algorithms developed in this field create a database by comparing the package inserts of drugs and prevent patients from using drugs that may interact with each other.
These and many more functions are being used in the health sector to make people's lives easier, to prevent or accelerate the treatment of diseases, and most importantly, to ensure that the right treatment is applied.
Artificial intelligence technologies are making human life easier. It is a well-known fact that human life expectancy has increased thanks to the advances in medicine over the years. The age we live in offers a very different future with continuously renewed developments in medicine.
Thanks to the use of artificial intelligence technologies in medicine, it is not difficult to predict that human life will be extended and the quality of life will increase. Thanks to these developments, perhaps a world devoid of disease awaits us in the future.
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