Artificial Intelligence: Is It A Gift Or A Curse To Medical Science?

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AI Is It A Gift Or A Curse To Medical Science?

In the field of computer science, artificial intelligence (AI) aims to create intelligent machines that can replicate human behavior. It is nowadays an essential part of the IT industry. AI was introduced as a concept that can mimic the human brain. It should have the ability to investigate problems related to the real world.

AI can store and process a large amount of data in an intelligent manner and translate the information to make functional tools.

Although the concept and application of AI are still in its infancy, still there is a gradual implementation of AI in the field of healthcare is being done. Making AI enabled systems for better diagnosis and treatment.

Opportunities in new AI technologies 

Unlike human beings new AI technologies can identify signs of illness in medical images much more efficiently and accurately.

For example, there is a deep learning algorithm designed and developed by a company. It was called Picture Archiving and Communications (PAC), it can detect signals of diseases in medical imaging modalities that include CT scan, MRI, ultrasound and x rays. PAC can compare the imaging data to the past images stored in a large database and by analyzing the ancillary clinical data and studies of the laboratory. As a result, it is claimed that compared to human radiologists PAC can achieve 50-70% more accurate data at 50,000 times faster speed. Diagnosing a particular disease is another key field in medicine where AI is making its impact.

This AI is enabled with modern technologies that can ingest and analyses and make a report on huge chunks of data across different fields to identify and guide the clinical decision. For instance, the graph-based analytics with risk prediction system by Lumiata has reported that it has injected more than 160 million data points from journal articles, textbooks, public data sets and other places to produce a graphical representation of the relationship between the disease and the patient.

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The newly acquired knowledge can help identify the different aspects of the disease and help to guide the development of new treatments. Big data also plays a key role here; complementary technologies that include ‘smart wearables’ have the ingredients to enhance the power of medical AI as it collects diverse health-related data directly from the user. With the combination of these technologies, it will enable researchers to move closer towards the ‘precision medicine’ which is an emerging approach to disease prevention and treatment taking the variety of genes, lifestyle, and the environment into consideration.

Another usefulness of medical AI is that it can cut the cost of hospitals that have to be spent for doctors and nurses and the overworks that they have to perform. Clinicians will be able to spend more time with the patients when human-delivered care is the key once the elements are automated. The focus will shift to working on more complicated cases, patient communication and clinical interpretation. Once these areas are benefited from AI inputs, together they can address a larger number of medical needs and improve the overall delivery of healthcare.

Risks Involved in Artificial Intelligence :

While we all are focusing on the various advantages of Artificial Intelligence and how beneficial it is to improve healthcare, they also come with some risks. Things like the clinical setting, the provision of healthcare and the data of the patients require utmost security, accuracy, privacy, and reliability. To preserve the trust in technology, consistent accuracy is required. However, AI has not evolved so much till date. Although AI can effectively deal with the comprehensive datasets, they may often come across some data and another kind of scenarios in a clinical setting that they are not trained on.

This makes them potentially less reliable and accurate which puts the safety of the patients at risk. As it has already been mentioned, the medical AI systems can work with the smart wearable that is consumer-facing and also makes use of the data generated by them. However, it has been discovered from a study that a popular wearable once provided invalid readings of heart rate which couldn’t provide a meaningful estimate of the heart rate of any user. Not only this but also the data which these devices collect are sensitive which must be safeguarded. Many fitness applications included a large number of confidential and high -risk data such as the financial information, health information, location and so on.

If the work is done from any such premise where the personal data is easily identifiable, all the data which is used in medical setting need to be safeguarded. There is a stark distinction between The nonclinical and the clinical use. There may be chances that the data from the smart wearable of the non-clinical part is fed into the clinical system of AI.  Hence, implementation of a clinical level of accuracy, as well as reliability, needs to be done. Security and accuracy are of utmost necessity to foster the trust in such new technologies.

There should be greater transparency in how the results are achieved; to state one such case, once an AI system effectively came to recommend that a person required mastectomy. AI is having a great impact in the field of health care. By this year, around 1.7 billion smartphone users will have access to health apps.

There has to be a combination of regulations and standards to ensure the reliability, accuracy, and security of the AI technologies which are used in medical fields.  The regulations framework which already exists should be developed.  AI programs are capable of learning and altering recommendations in such a way which has not been foreseen or recommended by the creators. Hence, there needs to be a regulatory framework which would help in shaping up and defining the guidelines.