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This article is written by Karan Gautam of 4^th Semester of Delhi Metropolitan Education

Abstract

The COVID-19 incident has brought to light some of the most important healthcare difficulties as well as the advantages that a thorough integration of digital and AI technology in the healthcare context may provide. Regulatory issues and policy initiatives, such as ownership and control of data, data sharing, privacy protection, telemedicine, and accountability, need to be carefully and continuously addressed even though medical solutions based on AI are expanding quickly. AI research requires robust and ethical guidelines, necessitating an update of the legal and regulatory framework around the world. Although they have a strong base, several recently suggested legal frameworks leave out several concerns that would make it difficult for algorithms to be fully trusted. To fully realize the potential of AI across health systems respectfully and ethically, there has to be an international effort for an open, responsible dialogue about the best way to prevent and mitigate potential hazards. National and international politicians, medical professionals, and experts in industry and academia in the fields of digital health and machine learning must participate in this discussion. The potential of AI in healthcare will be realized if this is done correctly and on schedule

Keywords: artificial intelligence, telemedicine, policy, ethics, healthcare, regulation, and accountability

Introduction

The art of mimicking human intelligence and behavior using computers is known as artificial intelligence or AI for short. Additionally, it teaches computers how to mimic human behaviors and decision-making. All sectors of the economy, as well as academia and government, have given AI a lot of attention. Situations change quickly in the healthcare industry, such as new virus breeds that cause terrible diseases. This ipso facto is what led to the development of medicinal treatments for such terrible infections. AI is only now starting to have a significant impact on the healthcare industry.

Healthcare is expected to be among the top 5 industries using AI as a key component of their operations, according to a recent McKinsey research. This paper is a small beginning in offering such information, keeping in mind that there are many genres that the healthcare business has not yet explored about AI.

AI’s current application in healthcare

The global adoption of new communication and information technologies, such as IoT (Internet of Things), AI, blockchain technology, and so on, is accelerating industrial and technical revolutions in the modern world. AI is now beginning to change the game in several areas of healthcare. Here are some of its highlights:

Drug discovery: AI-based solutions are being created to identify new possible treatments and therapies by examining massive databases of data on currently available medicines. To combat serious dangers that have emerged over the past ten years, such as the Ebola virus and the Coronavirus, this would aid in rethinking current treatment systems and medications. The success rate and efficacy of the corresponding drug evolution would be improved by AI, and it would also hasten the process of introducing new pharmaceuticals to the market to combat these terrible diseases.
Radiology: Robotic image analysis and diagnostics are being developed using AI-based technologies. This would increase efficiency by avoiding any kind of human error and assist in identifying the areas of focus in a body to the radiologist via a scan. The development of novel methods of cancer prevention is evidenced by recent advancements in the identification of tumors in the body using CT and MRI scans. Radiology is expanding in parallel with other fields at the same rate that AI is developing, and this growth is directly correlated with rapidly increasing processing and data capability.
Medication adherence: AI-based innovations are designed to enhance patient-doctor communication, track medication intake, and support increased adherence levels that lead to better clinical outcomes and a higher quality of life. For cell phones, a variety of AI-based applications that promote adherence have been developed. These apps serve as powerful tools for the patient and their family by providing quality-checked information about the illness, its effects, therapies, safety precautions, and other related topics. AI robot assistants are currently quite popular among diabetic patients for self-managing chronic conditions like diabetes and blood pressure.
The prognosis for infection rate: AI-based therapies have technology that can monitor the rate of virus spread, predict how it will evolve in the future, pinpoint patients at high risk, and create on-the-fly controls. By quickly identifying infections, this also lessens the workload for healthcare professionals and the risk to their safety, especially during epidemics.

AI-related difficulties in the healthcare sector

As we all know, for an AI-based solution to be successful, large amounts of patient data must be collected to train and improve the efficiency of the relevant algorithm. Giving machine access to these datasets in healthcare, however, can result in several problems:

a. It is strictly forbidden under healthcare regulations to access a patient’s medical records. Similar to previous years, a large amount of data was shared between businesses and hospitals as a result of AI companies entering the health industry. The patient’s right to privacy is being violated right here and now.

b. Accurate and reliable data are simple to obtain in other businesses. For example, it is simple to measure car position and velocity in the automotive sector to forecast traffic on highways. The correctness or measurability of data, however, is not assured in the field of healthcare. For instance, clinician comments in electronic medical records may be poorly formatted and difficult to understand and process.

c. When a patient and doctor connect, trust develops between them, making the diagnosis conversation simple and engaging. However, accomplishing the same with a machine can be challenging, and a patient and doctor’s connection to one another may suffer. Therefore, it would be challenging to embrace such cutting-edge equipment for patients and physicians.

Even though new, cutting-edge technologies are created every month, it is still difficult to create an AI system that is immune to fallacies. At the end of the day, it is a machine made by humans, thus it will never be able to completely replace people because the human brain is the greatest mystery in the universe and nothing can compare to its capacity for multidimensional thinking and learning.

The future of AI
For the future, the best promise of AI in healthcare is the hybrid model, where professionals take the main responsibility of patient care while receiving AI insights for diagnosis, risk detection,and treatment support. By assessing the associated risks, this will encourage patients anddoctors to use these tools anddoctors can easily work efficiently and identify who I am sick with. Beyond the aforementioned issues, AI is starting to make its way into healthcare and can now ease some of the burden on doctors. Patients who cannot go to a large the hospital can now be diagnosed remotely with expertise. It would be simple to expand effective medical services to underdeveloped areas. There is still more work to be done in AI, but the future of AI in this sector appears bright, attainable, and exciting. Additionally, using realistic simulations that give the impression of being in real-time, which even computer-driven algorithms can’t provide, would make training medical students easier and more fascinating.

Using AI in healthcare raises several legal and ethical issues.

It is important to remember that society faces the following legal and ethical challenges as a result of AI:

Privacy and surveillance issues,
bias or prejudice, and
the place of human judgment in the age of AI.

Data breaches are increasing as a result of the adoption of more modern digital technology in parts of daily life. It is important to emphasize that any error in the healthcare industry due to a procedural or regulatory lapse can have dire and potentially fatal consequences for the person whose data was stolen.

Patient privacy, both in terms of information provided by them and information gathered about them through inputs, must be protected because patients often interact with doctors at sensitive times. Concerns about the use of AI in the healthcare sector are growing as a result of the fact that there are now no clear norms or regulations that control it per se.

Laws Around the World Governing AI in Healthcare

Following is a quick summary of several major international laws governing the use of AI in healthcare:

European Union

The Resolution of the European Parliament was based on research that was commissioned and overseen by the policy division for “Citizens’ Rights and Constitutional Affairs” in response to a request from the Committee on Legal Affairs of the European Parliament. The need for developing a legal framework to control robots and AI that can adapt to any scientific advancements was emphasized in the paper. The report has made a significant contribution by outlining the actions that AI may engage in that may imperil citizens’ fundamental rights and place them in danger.

China

It’s noteworthy to note that no laws or regulations in effect in the People’s Republic of China accept the term “digital health.” However, the government has correctly developed several healthcare regulatory frameworks related to digital health, including the Regulation on the Administration of Medical Information and Administrative Measures for Internet Hospitals.

India

Even while cyber risks and privacy violations in the healthcare industry and other digital areas continue to affect India, it is the democratic country’s own Constitution that recognizes privacy as a basic right under Part III, as stated in Article 21. The Information Technology Act of 2000, the nation’s 20-year-old IT law, is still in force as it waits for the dawn of new data privacy and protection regulations.

Conclusion

The need for delivering new and innovative solutions in healthcare is obvious given the myriad problems that must be resolved, guided by factors like the rising incidence of chronic diseases, the aging population, etc. that are well-documented. Despite the media attention they deserve, AI-based solutions have made only modest progress in addressing major issues and still have a long way to go before they can have a significant worldwide impact on the healthcare sector. If the approaching, significant difficulties facing the healthcare sector are successfully addressed by AI, this might have a significant effect on the sector’s future operations, resource augmentation, and patient outcomes assurance.