The implementation of artificial intelligence across all walks of life is pushing the boundaries of what’s possible. What seemed like science fiction not so long ago is now absolutely real. The application of artificial intelligence methods in medicine is an extremely promising direction. Over the last five years, the number of cases using robots for diagnosis and treatment has increased tenfold. The achievements made possible by the application of machine learning in this sphere make the widespread implementation of artificial intelligence in medicine a reality. This article will examine the tasks AI performs in medicine, future prospects, and the challenges that scientists have encountered along the way.
The Application of Artificial Intelligence Methods in Medicine
Artificial intelligence elevates the level of treatment and diagnostics to a new tier. Robots have become a reliable assistant to doctors in many areas:
- Robots assist surgeons during complex operations. Unlike humans, they can repeat the same actions indefinitely without rest. This is especially important when surgeries last for many hours. Scientists conducted a study and discovered that the likelihood of complications after surgeries involving robotic technology is five times lower. Robots are indispensable assistants to doctors, but the talk of AI machines conducting operations independently without human participation is still premature. The technology is not perfect yet and could make mistakes leading to fatal consequences.
- In the field of therapeutic treatment, artificial intelligence is used to determine medication dosages with maximum precision. The use of AI avoids errors when prescribing dosages. As a result, treatment becomes more effective and clinic expenses are reduced. The technology of personalized parabolic dosing is based on the patient’s reaction to the medication. The system forms a two-dimensional parabola to determine the next dose. This scheme is universal and works regardless of the disease and medication, so its application prospects in the therapy of any disease are quite extensive.
- In the realm of diagnostics, AI proves to be a reliable doctor’s aid. There are computer assistants that help patients with self-diagnosis. Communicating with the chatbot, the user describes the symptoms in detail. Based on this data, the robot provides detailed information about the patient’s health condition. Of course, there’s always the risk that the patient will incorrectly describe the symptoms or deliberately try to deceive artificial intelligence. Therefore, a diagnosis made by a computer assistant cannot yet be considered final and requires further examination. An extremely promising direction is the use of AI for early diagnosis of oncological diseases. Scientists were able to create an algorithm for the analysis of MRI images based on artificial intelligence. This improves the chances of detecting cancer at an early stage when there are high chances for a complete cure.
- Patient care becomes easier with the use of mobile software based on AI. Nurses and caregivers use such applications to find an individual approach to each patient. A series of similar solutions are designed for use by patients with limited mobility. The system reminds them to take medication on time, helps contact specialists to quickly get a consultation, etc.
There are many more areas in medicine where AI’s help is already widely used. For instance, in monitoring pregnant women, the system can help notice deviations from normal fetal development indicators. AI is also used to create new drugs, assess the effectiveness of medical equipment and medications, and identify the causes of diseases.
Tasks of Artificial Intelligence in Medicine
AI in medical institutions is used to solve the following tasks:
- Early diagnosis.
- Accurate dosage prescription. Determining the optimal treatment scheme.
- Conducting surgeries with a high level of precision.
- Remote preliminary diagnosis assistance using a chatbot.
- Identifying the real causes of diseases.
- Reducing the cost and improving the quality of treatment.
- Simplifying documentation processes in healthcare institutions.
- Determining optimal pricing for medical services.
Prospects for Artificial Intelligence in Medicine
The following areas are considered the most promising for the application of AI in medicine:
- The use of microrobots for minimally invasive procedures. In 2022, scientists introduced a unique crab-like robot to the public. Its thickness reaches only 0.5 mm. In the future, these robots will become even smaller, and their application possibilities will broaden.
- Diagnosis of diseases without human involvement. Soon, robots will be able to make not approximate but precise diagnoses by analyzing examination data.
- Conducting surgical interventions. Once the technology has been perfected, robot surgeons will be able to not only assist specialists but also perform operations independently.
- Medical sorting. A robot will be able to quickly analyze information about patients arriving at the emergency room. This will solve the problem of prioritization. Help will be provided first and foremost to those patients whose condition is most serious.
Artificial Intelligence in Medicine in Russia
In the last few years, Russia has seen intensive integration of AI-based technologies into healthcare. The pandemic significantly accelerated this process, highlighting issues that are successfully resolved through the use of artificial intelligence.
Dozens of hospitals in Russia are already actively using digital equipment that utilizes AI. The federal program “Artificial Intelligence” aids in implementing specific projects in this field.
In Russia, the most popular AI-based technology is computer vision. It recognizes information in images so that doctors can make more accurate diagnoses. Computer vision is an effective tool for analyzing fluorograms, radiograms, mammograms, and CT scans.
Challenges of Artificial Intelligence in Medicine
The active advancement of artificial intelligence in medicine has revealed the following challenges:
- Erroneous diagnosis. Even minor inaccuracies in input data can lead to completely incorrect diagnoses.
- The accuracy of image recognition is still not high enough. Image distortions, which a doctor would easily identify, can be misinterpreted by the software as changes in the patient’s tissues.
- Medical institutions are hesitant to fully engage the capabilities of artificial intelligence. Clinic directors and officials fear the responsibility for possible errors when using new tools.
- The system for protecting patients’ confidential data, accessed by robots, needs further refinement.
Conclusions
Artificial intelligence in healthcare has the potential to raise the quality of treatment to a new level, increase patients’ life expectancy, and reduce mortality. The technology continues to evolve, and in the future, its capabilities will expand to encompass all areas of medicine.
