Artificial intelligence and the world of medicine in the post-Covid-19 world

Covid-19 taught the whole world a great lesson: the special need for a strong infrastructure in the field of medical care and treatment. By providing a suitable, low-cost and scalable solution for the medical community, we can hope to improve the quality of access to medical care around the world and be more prepared to fight widespread and deadly diseases.

\n

Meanwhile, artificial intelligence and machine learning have shown that reaching such a vision is not impossible. The rapid development of artificial intelligence has made doctors and patients much more hopeful to optimize people’s health. Artificial intelligence is expected to make everything simpler and more efficient, from treating various diseases to processing health insurance.

\n

In this article, we will discuss the impact of artificial intelligence on the world of medicine in the post-Covid-19 world.

\n

Artificial intelligence, the savior of the post-corona era

\n

\n

Artificial intelligence and machine learning have become very important in today’s healthcare world. More accurate diagnosis of people’s diseases, data analysis for more effective drug treatment plan and prediction of high treatment costs are among the most useful applications of artificial intelligence in the field of health. Given the growing impact of artificial intelligence in the healthcare world, here are some of the biggest AI trends during the COVID-19 pandemic and beyond.

\n

Machine learning helps identify patients at risk

\n

Machine learning has a significant impact on identifying patients at risk and, of course, improving the diagnosis and treatment of their disease. In the medical world, huge amounts of data are usually generated. Artificial intelligence and machine learning help medical centers and health insurers gather actionable information from medical records stored in databases and distributed sources. Machine learning models that are designed to analyze images and information, use this information to help doctors in early disease diagnosis. As a result, doctors can create preventive treatment plans for patients, achieve better results in the treatment process, and follow preventive processes more effectively.

\n

Mobile phones and smart gadgets help the treatment staff and patients

\n

Mobile phone applications and smart gadgets can create a precise and appropriate approach to care for patients and accelerate their recovery. Currently, many patients use smart watches to view their health data. Therefore, gadgets are expected to become an efficient tool for using machine learning in healthcare. Machine learning models along with smart phones help nurses to more accurately identify abnormalities related to medication and patient medical care at home. This technology is very efficient especially for patients who do not follow their treatment process properly. In this way, the doctor or nurse can remotely monitor their recovery process and help them along the way.

\n

Health insurers are using data analytics to cut costs

\n

Machine learning models help health insurance organizations identify unusual patient requests. This process helps them to reduce insurance costs and medical service costs in the long run by accurately and correctly evaluating these requests. Of course, statistics show that these people are only about 0.16% of the total insured, but they account for 9% of the total medical care costs. Due to the huge volume of medical claims files, health insurance providers are increasingly turning to machine learning to better identify these patients.

\n

Aside from insurance organizations, nurses and doctors use these machine learning models to make more accurate diagnoses, refer to specialists, and monitor recovery. These measures are carried out with the aim of improving the patient’s overall health and preventing situations where the patient needs expensive medical care. Significant reduction of medical costs and improvement of patients’ health probably in the long term will make insurers, hospitals and medical centers use machine learning more. Probably, in the future, more sophisticated artificial intelligence models that use medical record data more accurately and better will increase the efficiency of this approach.

\n

Artificial intelligence is democratizing the healthcare industry

\n

With the increasing use of artificial intelligence and machine learning in medical care, it is expected that in the long term more people in the medical community will be able to run machine learning models without expert help. Newer tools have a simple user interface and present the results of the collected data analysis in a clear and specific way. It is expected that by using this approach, doctors and nurses can better understand the data and their impact on patient care.

\n

Will artificial intelligence replace doctors and nurses in the post-Covid-19 world?

\n

It is hopeful that the medical world is well aware that machine learning and artificial intelligence are not going to replace doctors and nurses; Whether in the post-corona era or even in the distant future. The idea of ​​replacing doctors with artificial intelligence remains at the level of science fiction for now. What the approaches of intelligence have shown is that activists and experts in the field of health can make more decisive and correct decisions for the process of diagnosing and treating people’s diseases by using artificial intelligence and machine learning systems, and be more prepared to fight against epidemics and deadly diseases in the future. .

\n\n