AI applications in medicine and their impact on society

The use of new technologies and artificial intelligence (AI) has meant a before and after for many sectors. One of them has been medicine, where the latest advances and applications have been influenced by the development of technology. Artificial intelligence is a specialty in the field of computer science that is used to produce programs through a series of algorithms that have the ability to think, learn and make decisions, as humans do.

How does AI work?

AI began to be developed in the 1990s with the aim of creating a computer system that would process data in a similar way to the human brain. One of the branches of artificial intelligence that is most useful in the healthcare sector is the automatic learning. This system has the ability for machines to use the algorithms and learn from the dataThis improves decision making with the processed information.

By automating functions and tasks, healthcare professionals can process and analyze medical data faster and more accurately. This has a significant impact on the different areas of the health care sector and promotes improved healthcare management. Among the main uses offered by AI in the healthcare field, we find that it helps to develop and optimize processes in clinical diagnosis, disease detection and prevention, healthcare, research and the creation or updating of new drugs.

In turn, it has also been a determining factor in the progress of telemedicine and in the development of personalized medical treatments. In the following article, we address the main applications of AI in medicine and how they are helping to create a more complete, agile and effective healthcare system.

AI applications in medicine

In recent years, AI has been incorporated into medicine to promote higher quality patient care, speed up processes and achieve increased diagnostic accuracy. What are the different areas in which artificial intelligence is currently being used and what improvements have they brought about?

Disease prevention and early diagnosis

AI is a key tool in disease prevention. Through the use of Big Datawhich consists of a combination of digital health data, genomic data and patient behavioral data, can be used as a basis for the development of a new identify risk factors and patterns that lead to the development of certain diseases.

• Spread of diseasesOn the one hand, machine learning algorithms can predict the spread of diseases such as influenza or COVID-19, anticipating epidemic peaks and allowing preventive measures to be taken.
• Detecting signs of chronic diseasesAnother of its applications is that early signs of chronic diseases, such as diabetes or heart disease, can be identified. Chronic diseases are characterized by their slow onset and, in most cases, go unnoticed until they develop into more serious complications. Therefore, the use of AI is very useful for detecting possible signs of disease in medical studies, such as blood tests, ultrasound images or electrocardiograms. In this case, AI algorithms can detect patterns of cardiovascular disease through medical images such as the magnetic resonance imaging or computed tomography scans.
• Predisposition to genetic diseasesThrough the use of genomic data, artificial intelligence can also analyze predisposition to genetic diseases. AI algorithms are responsible for studying patterns in DNA to identify genetic variants that could indicate a high risk in the development of certain diseases. In oncology, it is used to predict the risk of breast or colon cancer, allowing doctors to design personalized prevention plans.

Clinical diagnosis

In the image processing and interpretation for diagnosisAI offers algorithms that improve the quality and accuracy of clinical diagnostics. They allow to recognize complex patterns in image data automatically, to eliminate noise to increase their quality and to establish three-dimensional models from images of specific patients. In this field, we can highlight the research by IBM researchers on a new study on the use of a new AI model can predict the development of malignant breast cancer.

With rates comparable to those obtained by human radiologists, this algorithm can learn and make decisions about cancer development from imaging data and patient history. Specifically, it was able to predict the 87% of the analyzed cases and was also able to interpret the 77% of noncancerous cases. Therefore, this model could be a fundamental tool to help radiologists confirm or dismiss positive cases of breast cancer.

Personalized medical treatments

Another use of AI in medicine is to find personalized medical treatments for each patient. Based on a set of factors, such as medical history, lifestyle and genetics, the AI algorithms can analyze a large volume of genomic and biomarker data to identify patterns and risk factors.

This can be used to develop a specific medical treatment for the patient's needsThe use of AI in oncology, for example, helps to identify the best treatment for each type of cancer, taking into account the specific genetics of the tumor. For example, in oncology, AI helps to identify the best treatment for each type of cancer, considering the specific genetics of the tumor.

Health care

Patient care is one of the areas where AI can provide great support to both medical professionals and patients. In this case, the AI-based virtual assistants are an ideal solution for automating functions and tasks. These include the appointment management, the realization of basic health consultations, the symptom assessment and the administration of medications.

Promoting telemedicine

These systems have also enabled the evolution of telemedicine. In this sense, professionals can monitoring patients suffering from chronic diseases remotely and receive alerts of possible anomalies that may arise in their health condition. This offers wide-ranging benefits in reaching a larger number of patients, especially those who live in regions that do not have all the health services in their localities and must travel to receive medical care.

Resource management in medical centers and hospitals

Another area where AI can be implemented is in the management of material and human resources in clinics, hospitals and health centers. Examining large amounts of data from historical records can be essential for to foresee the resources required in a given situationThe company's management and optimization of the available resources can be very helpful for the management and optimization of the available resources. This can be of great help to avoid overcrowding of medical centers at times of high demand and be able to manage the inventory of medical supplies and the availability of beds and medications.

Drug research and development

Artificial intelligence has been fundamental in the development of medical research, both in the development of new drugs as in the optimization of clinical trials. The integration of artificial intelligence into drug design involves a multidisciplinary approach combining both chemistry and biology concepts as well as computer science. to accelerate the discovery of new treatments and medical solutions.

For this purpose, AI models created with machine learning and deep learning algorithms are used to analyze large amounts of data on chemical and biological compounds and the interaction between them.

Robotic surgery

Robotic surgery systems such as the Da Vinci use AI to perform complex surgical procedures with greater control and precision. These robots are controlled by the surgeons to make small incisions, which helps to reduce the margin of error, perform minimally invasive surgeries and improve patient recovery times..

Another key area in which artificial intelligence can be applied is in the creation of customized surgical plans. In this case, the following are used data from previous surgeries to optimize techniques and to predict possible complications. that may arise during operations.

Training

AI has a key role to play in the training of health professionals. It provides multiple tools that help medical specialists to acquire and perfect their skills in different areas, increasing their knowledge in a more efficient and personalized way.

On the one hand, the medical simulations through AI allow students to be able to implementing complex procedures and reducing the risk of errors. At the same time, the following stand out learning platforms that use AI to adjust educational content based on the level of knowledge of the learnerThe aim is to achieve greater efficiency in the learning process.

In summary, AI has a wealth of applications in medicine and there are new improvements and innovations every day that help to further advance the healthcare sector.

Kiko Ramos

CEO of 4D Médica. Expert in marketing and distribution of medical equipment.