From Big Data to Artificial Intelligence that will change our healthcare life in future

New technologies have developed new ways of storing data so that any person is able to generate and share diverse content in a massive way, where big data is now a challenge for companies that try to store large volumes of data, classify them, interpret them and turn them into useful and manageable information (Jiang et al., 2017).

This large volume of information has grown due to social networks and the speed of broadband. It also influences the variety of data that we have to interpret and order, such as gender, marital status, employment situation, geographical situation, interests, tastes, age data, etc. The useful life of that information is very important. Data that has become obsolete will not be preserved. One of the keys to storing so much information is to keep it in force.

The Big Data opens the way to a generation of new companies that have different types of professional profiles that are responsible for the extraction of data to achieve fruitful results for companies.

Discover the advantages and benefits of big data applied to healthcare

Some of the benefits of Big Data in healthcare management are:

· Competitive advantages in the big distribution: it allows to update, optimize and refine inventories according to the demand in real time.

· Improved efficiency and costs: Big Data analysis can accelerate the speed with which a product develops.

· Improved health business management: in addition to optimizing the supply chain and inventory, Big Data can be useful to reduce the cash conversion cycle, control risk factors and make business decisions.

· Cloud storage: One of the problems in managing high volumes of data is the high cost of storage infrastructure. The result is that it can be accessed through applications designed to handle large volumes of data and solutions can often be obtained in real time in a simple way.

Big Data and Health

Big Data is the management and analysis of huge volumes of data that due to their size cannot be treated in a conventional manner. These data are converted into information, thus helping to make strategic decisions in companies, organizations or governments. This technology can ensure that the processing of data, for example, in the case of health provides many benefits to the health system itself and its main players. Some considerable improvements in this area of ​​health could be:

· Optimize data storage

· Improve clinical management

· Favor research

· Reduce costs

· Advance solutions

· Foresee possible problems

· Improve the coordination of citizen attention

· Fight against fraud and abuse

· Reduction of administrative and clinical inefficiencies

Big Data represents an opportunity for innovators and everyone who cares about health increases the possibility of obtaining more effective information from the data and lower mortality rates in patients. It will be used to predict, prevent, and personalize diseases. Health professionals, for example, can use big data analytics in real time to know where and at what pace a flu virus is spreading, and can adopt a rapid response and guarantee the stock of vaccines in the necessary areas (Manogaran & Lopez, 2018).

Specifically, the greatest challenges in the investigation of the genome and its sequencing are being found. This is a breakthrough for medicine and future healthcare. A very revealing fact is that a year ago, sequencing the human genome cost a trillion dollars, a few months ago the company Life Technologies presented a proton capable of sequencing the entire human genome in one day for US$1,000. This is expected to continue to drop to a few hundred dollars. It is not about knowing our DNA, but about hundreds of millions of people and the possibility of crossing all these data. Now, people can change their genetic profile with the data of the day to day and the environment that surrounds them to be able to know perfectly, the risks of suffering from cancer, diabetes or heart disease. All this will take us to personalized medicine. We can know the correct treatment for a specific patient at the right time. In addition, the impact on cancer treatment can be spectacular and this wealth of genomic information will allow the discovery of new drugs.

Artificial Intelligence and Healthcare

Modern healthcare has no boundaries, it is able to provide the necessary medical care to anyone at the right time and in the right place. The leading role in its transformation is played by digital technologies, for which distances and time frames are irrelevant. Their use gives countries tremendous opportunities to solve the urgent problems of the population in the field of health protection.

One of the most discussed topics in the world is artificial intelligence (AI) and its application in various fields including healthcare management. Health systems face challenges worldwide. This is an increase in population and life expectancy, which increases the number of people suffering from chronic diseases. WHO estimates that by 2035, there will be an estimated 12.9 million skilled doctors, midwives, and nurses in the world (Chen et al., 2017).

The amount of data stored in digital formats has increased hundreds and thousands of times. However, only part of this data is used to improve the quality and effectiveness of medical care, since they are not systematized. In addition, the explosive growth of medical data is not limited to the health care system. With the introduction of smart digital products and services, more and more data about their health is collected by patients themselves. Moreover, gadgets are getting more and more intellectual functions and capabilities for analyzing data and the possibilities of monitoring the patient’s condition outside the medical institution. The world will have to decide how to make this data useful (Jiang et al., 2017), however, the data is obtained and accessed usually without the conscious knowledge and approval of their consumers. This is the major factor that has raised ethical concerns among several leaders and experts about the extent of the personal information that can be accessed, as well as the safety and wellbeing of the common people who are unaware that their personal information is being obtained, accessed, and used (Leung et al., 2020).

Artificial intelligence can improve the efficiency of workflows, help in making clinical decisions, empower patients to actively manage their health, and also ensure the management of public health in general. In near future, it will help doctors quickly make decisions for individual patients, provide information that is not visible to the naked eye, make a primary diagnosis and prescribe an individualized treatment with the best outcome for the patient. It will also make hospital workflows more efficient, freeing medical workers from routine and repetitive work. Likewise, it will be able to notice in time the deterioration of the patient’s condition and select the treatment tactics or suggest an adjustment to the one already prescribed.

One of the latest achievements is an angiograph equipped with augmented reality digital technologies, which allow doctors to see the final result on the screen depending on the course of the surgical intervention. Lastly, using artificial intelligence, the world’s first spectral computed tomography scanner provides not only detailed visualization but also the composition of the tissues. In recent years, ultrasound diagnostics in the tablet has become a reality — outside the walls of medical institutions by pressing one button in minutes.

References

Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., … & Wang, Y. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and vascular neurology, 2(4), 230–243.

Chen, M., Hao, Y., Hwang, K., Wang, L., & Wang, L. (2017). Disease prediction by machine learning over big data from healthcare communities. IEEE Access, 5, 8869–8879.

Leung, K. T. Y., Antoś Dembicz, & Anne Stevenson. (2020). Exploring Ethical Dilemma in Big Data Analytics: A Literature Review. Technium: Romanian Journal of Applied Sciences and Technology, 2(5), 43–48. Retrieved from https://techniumscience.com/index.php/technium/article/view/891

Manogaran, G., & Lopez, D. (2018). Disease surveillance system for big climate data processing and dengue transmission. In Climate Change and Environmental Concerns: Breakthroughs in Research and Practice (pp. 427–446). IGI Global.