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Computational Technologies for Healthcare

Sathiyaraj, Assistant Professor, GITAM School of Technology, GITAM University

In the modern-era technologies are evolving at a faster rate, resulting in a transformation of our lives, particularly in healthcare, with the objective of saving humanity while also providing advanced solutions for practitioners to enhance their choices. Artificial intelligence, Big Data Analytics, Internet of Things, and machine learning all have significant implications in accomplishing this. This article begins by outlining contemporary computational technologies in healthcare before discussing their significance and use. The technologies that are assisting healthcare to improve will indeed be discussed in this article, which will then explore the several research possibilities and obstacles associated with implementing computational technology in healthcare.

Introduction:

Health care has greatly improved aid to automated systems assisting clinicians in making precise diagnoses and a better organizing of information system. Machine learning, artificial intelligence (AI), the Internet of Things, and data analytics are all important in the healthcare business. Machine learning algorithms, for an instance, detect heart disease and cancer at their earliest stages in addition to assist practitioners in making appropriate decisions and diagnoses. With the advancement of AI algorithms, the medical sector is gaining assistance for more successful surgery.  Data analytics and IoT plan to handle data effectively and remotely, allowing doctors to access patient reports from anywhere and at any time. More significantly, to forecast health outcomes and make informed treatment plan decisions. This had also improved as a result of counselling patients to visit physicians depending on their health status. Fig. 1 depicts the several aspects of emerging computing technologies.

Healthcare is an ever-changing and dynamically evolving industry. It is critical to stay up to date on the latest trends and advances, particularly for professionals or for the general public. There are numerous elements at work, including the obstacles, changing lifestyle, extended lifespan, evolving health care systems, and digitization. Everything has led to a rapidly changing healthcare scene. Thus, learning about upcoming trends can assist organizations in analyzing, identifying discrepancies and gaps, and resolving those difficulties. We can also estimate what the main players in the healthcare industry will do this year. Healthcare technology trends possess the potential to significantly transform the industry.

 Image depicting the evolution of digital transformation: strategy, execution, analysis, and refinement.

Fig.1 Role of Computing Technologies in Healthcare

Related Work:

Various advancements in how we identify, prevent, and diagnose diseases have driven the healthcare business during the previous decade. Without the phenomenal growth of technology fueled by AI and the digital transformation of healthcare services in response to tougher global conditions and increasing needs for accessible and excellent medical care, this should not have occurred.  From anaesthetics and antibiotics to MRI scanners and radioactive therapy, technical advancements in healthcare have resulted in profound transformations. While technologies, the latest pharmaceuticals and treatments, novel devices, updated social media helping with healthcare, etc., will fuel innovation, human aspects continue to be one of the consistent limitations of breakthroughs. No prediction will delight every person; rather, this article intends to investigate snippets of the future to see ways in which we can speculate a bit more clearly about the best way to go where we would like to go.

The intent of this article is to explain the tactical approach to transformation. The use of digital health technologies in healthcare organizations is more significant because improving healthcare, exchange of information, and the efficiency of systems, particularly in developing countries, is crucial to achieving the Millennium Development Goals. The purpose of the research is to highlight the variables of growing technology usage that influence the transformation of healthcare. This technological innovation effectively manages the records needed to record transactions and procedures. Healthcare providers have little choice but to adapt to the fast-moving technological change in the health industry if they want to stay competitive.  Artificial Intelligence, Internet of Things, Big Data, Machine Learning and Cloud Computing. It is crucial that those who must use the technology accept it and gain a deeper grasp of the elements that contribute to the systems' positive effects in order to enhance the deployment process. Essential to society's health and the standard of care. Therefore, these justifications suggest that healthcare providers are currently adopting digital transformation in healthcare units. The advantages of digital transformation in healthcare organizations are very strong. They consist of decreased travel expenses for employees, less time spent away from patients, and simpler information system wait times in the healthcare industry.

In recent days, the entire nation has been pushed down by Corona virus. Techniques using both traditional and cutting-edge technologies are required to combat COVID-19 and bring the situation under control. The article focuses to methodically examine current developments in smart healthcare technologies, such as big data analytics and artificial intelligence, which will ultimately rescue the planet. By creating connected frameworks, these intelligence-based solutions support creative managements, versatility, productivity, and efficacy. The research being investigated specifically addresses Big Data and AI contributions that ought to be incorporated into intelligent healthcare systems. Additionally, it investigates how big data analytics and artificial intelligence are used to provide users with information and assist them in making plans. Finally, it proposes models for intelligent healthcare systems that utilize big data analytics and AI [1].

a diagram showing the four components of a smart health system

Fig.2 Primary Technologies in Smart Healthcare

According to the Heart Attack & Stroke Stats 2021 from the American Heart Association (AHA), coronary artery disease and stroke remain the leading cause of death globally and are spreading at an alarming rate.  The current coronavirus (COVID-19) epidemic has made this increase much worse and put more strain on the already overburdened healthcare system. The common healthcare issues can be resolved using Smart and Connected Health.  Figure 2 outlines the most significant technology. Through incorporating services that are worth more, medical care can become more proactive, preventative in nature, and individualized. Effective use of intelligent health care facilities was made at several pandemic response stages, encompassing identifying diseases, viral being detected, individual observing, tracking, and regulating, as well as the allocation of resources [2]. It's critical to monitor the developments affecting technology in health care as we advance. Sophisticated hospitals and healthcare facilities rely significantly on legacy hardware and software, but it's important to consider how this equipment might be merged with contemporary hardware or ultimately replaced by more reliable ones. Without sacrificing predictability or connectivity, enhancements in efficiency, earnings, reliability, and privacy should take precedence.

Computing Technologies:

The trending technologies in the healthcare domain are discussed below and the digital transformation is depicted in Fig. 3.

Artificial Intelligence:

Healthcare uses artificial intelligence to assess and reduce several diseases' treatments. In a number of medical environments, including diagnosis processes, companies that manufacture medicine, portable medical facilities, etc., Intelligence is used. Intelligence assists in the gathering of historical information for illness identification and avoidance in the healthcare industry through digital health records. Besides pandemic therapy and consequence, artificial intelligence has a variety of other applications. The speed at which data is analyzed and judgements are made has been greatly accelerated by AI. Machine learning has a significant impact on the medical sector's capacity to develop new drugs and enhance the efficacy of testing methods.  The examination of CT scans is currently aided by artificial intelligence in order to detect pneumonia in COVID-19 treatment patients. Microsoft developed Project Inner Eye, an artificial intelligence radiological technology. It now takes only a matter of seconds instead of hours to complete the patient's 3D sculpting. To gather biomedical dissertations from PubMed, Microsoft has developed another artificial intelligence dubbed Project Hanover. It also helps in selecting the best treatments for every individual, as well as speeding up the cancer diagnosis process.

Internet of Medical Things (IoMT):

One of the most important breakthroughs in digital health care system is the Internet of Medical Things, which is one of the leading healthcare technology trends for 2023 that everyone in the sector should be aware of. The world economic internet of things (IoT) in healthcare market was estimated to be worth $180.5 billion in 2021, and Precedence Research predicts that it will grow to be worth $960.2 billion through 2030, with a compound annual growing rate of 20.41% since 2022 towards 2030. The development of healthcare information technology includes a significant number of wearables and trackers. Its main advantage is that they give clinicians access to accurate, real-time information about patients' health conditions.

A major change in patient consciousness is made possible by IoMT. Those who use trackers have access to real-time information about their daily activities and can suggest modifications along the way. The device can reciprocate patients and boost their incentive to live a better lifestyle if it has specific gamification elements. Because of this, technology has a significant impact, enhancing a reasonable drive to maintain healthy behaviors with sheer enjoyment.

Practitioners can now more fully involved in their patients' care and receive alerts at the right time. The extensive data collection generated by these innovative medical technologies includes information such as average activity level, dietary habits, and insomnia. With this knowledge, medical professionals may develop more authentic coaching programmes and precisely monitor the course of treatment.

Chronic Conditions and Wearables:

For treating diseases that necessitate considerable lifestyle changes, IoMT technologies shine. For instance, they include type 2 diabetes, obesity, and disorders of excessive worry. The most recent statistics show that there are 422 million diabetics globally. However, doctors were unable to trust the patient's statements and pledges because therapy for type 2 diabetes had been on their minds for a very long time. Healthcare practitioners lacked the tools to manage the progression because success is primarily dependent on dietary and lifestyle modifications. This issue has been resolved by the addition of wearables, which encourages doctors to work with their patients to develop better lifestyles. It helps set the foundation for informing patients about the stages and milestones of their therapy, or the "Patient First Approach." From 2022 to 2030, the market for personalized medicines is projected to increase at a compounded yearly growth rate of 6.95%, from a market size of $514.33 billion in 2021.

Fig.3 Digital Transformations in Healthcare

Remote Patient Monitoring:

Perhaps the newest developments in health technologies are hands-free communication, which will gain popularity over the coming years. Patients who are unable to physically attend doctor visits are receiving critical care under the pandemic's present conditions thanks in large part to remote monitoring. Telepsychiatry focuses on using technology to deliver mental health services, such as messaging and video conversations. It is anticipated to play a significant role in addressing mental health difficulties in 2023. Amongst recent developments in healthcare, remote monitoring of patients stands noteworthy. COVID-19 also contributed to the widespread adoption of monitoring patients remotely in the healthcare industry nowadays. Virtual care is more common because to online scheduling, remote treatment, and videoconferencing, to name just a couple of them. The range of IoMT devices also gives remote monitoring of patients even more possibilities. By 2027, the global RPM systems market is expected to be worth approximately $175.2 billion, up from $53.6 billion in 2022, according to the research firm Research and Markets.

Big Data Analytics:

The adoption of AI technology in the analysis of healthcare data is expected to save the sector at least $150 million by 2025, according to a prediction by Frost & Sullivan. Real-time and remote patient data analysis and measurement have made such an accomplishment possible. Given its astounding cost-effectiveness, the AI movement will take off in the following few years. The COVID-19 pandemic highlighted data analytics as well as the enormous difficulty of making real-time decisions in a rapidly changing environment for medical professionals and researchers. When done manually, numerous of sheets and discussions can ensnare healthcare providers. Because of this, the digital future will unavoidably feature technology that can handle Big Data without the assistance of humans and offer real-time analytics to decision-makers. Analytics' capacity for prediction-making is another strength. Forecasting analytics and operational intelligence improvements in this situation make it possible to use data-driven insights from prior patient contacts with healthcare organizations and make the necessary changes. It benefits both parties. Patients receive quick care and precise treatment regimens. As a result, healthcare providers benefit from optimized staffing and improved supply chain management.

Predicting Analytics Impact in the COVID-19 Disease outbreak:

Predictive analytics' full potential is now being revealed as a result of the pandemic. Strategies like the University of Chicago Medicine were created in response to the need to monitor and address community health concerns, enhance patient outcomes, and work with public health organizations. With the help of unique dashboards for data visualization, they offer new ways to use data.

In times of uncertainty, the technology can identify drug and equipment shortages and alert medical professionals to the issue. It additionally assists in monitor populations of patients, digital health trends, and ventilator and ICU demands. Additionally, predictive analytics incorporates outside data into the analysis, such as weather conditions. This acts as the essential crisis management optimization system and is GPS-enabled.

Predictions and Decision-Making:

The quantity of health-related sources of information used by organizations will skyrocket as the adoption of medical IoT solutions increases. What does this entail for medical professionals?.

In order to automate the collection and dissemination of such data throughout their business, they need search for cutting-edge platforms. Fortunately, predictive analytics in healthcare are anticipated to become increasingly ubiquitous and advanced starting in 2023 and continuing through 2028. The current difficulty in healthcare is obtaining accurate and thorough data. However, improvements in data quality and accessibility are anticipated this year because to developments in electronic health records and data exchange between healthcare organizations. Better forecasts and more reliable predictive analytic models are going to arise from this. Furthermore, advances in machine learning research enable healthcare systems to examine massive volumes of patient data in order to spot trends and make predictions. The combination of ML and healthcare technology can result in more precise diagnosis, individualized patient care, and ultimately better patient outcomes.

Health Care professionals Using Clinical Automation:

Healthcare spending are not to be taken lightly, hence why automation is crucial. Automation aids in cost-cutting, process simplification, and patient experience enhancement. Automation is anticipated to play a momentous role in the healthcare area in 2023. By the end of the year, it is anticipated that investments in automation technologies, such as robotic process automation, would account for more than half of all healthcare IT expenditures.

Privacy and Security in the Digital Realm:

Cybersecurity will continue to be a prominent trend in the health information technology business for a very long time because data security is still a major industrial concern. Future technology advancements will all adhere to the need for a strong security layer. The protection of confidential patient information given online is the ultimate goal. By the end of 2021, there were an average of 626 attacks on healthcare organizations per week, and that figure is still rising. In 2021, the US Federal Bureau of Investigation reported that over 40 million patient health records had been exposed due to the vulnerability of 50% of internet-connected hospital equipment.

IoMT device connectivity, network threat detection, and the use of powerful AI models to avoid the need to exchange patient data while studying it are some examples of contemporary cybersecurity solutions. Through the same, anyone can apply these incredibly useful suggestions to defend against cyberattacks. Still, given the prevalence and dangers of data breaches, cybersecurity is a popular topic. For instance, the top story today is about cybersecurity for hospitals. The situation will only get worse as information exchange and interoperability expand. Given the current situation, the healthcare sector will aggressively look for software in the upcoming years that is genuinely secure, dependable, and adheres to patient safety regulations.

Migrating to the Cloud:

The transition to the cloud for medical services is presently well beneath direction, and over the years to come, it is anticipated to accelerate dramatically. Markets predicts that the global medical cloud computing sector will increase from a projected $39.4 billion in 2022 than $89.4 billion through 2027 with an annualized yearly rate of development of 17.8%. This fixes many important problems with the delivery of services, including keeping records, providing care in instantaneously, and helping those who have financial resources that are scarce. Worldwide, providers employ the cloud to manage communications and digital health records efficiently as well as to arm medical personnel with factual information.

Robotic Process Automation:

This is among the latest medical technology developments that is gaining ground quickly. By 2035, the World Health Organization (WHO) projected that there would be 12.9 million fewer healthcare workers worldwide, making in-person doctor visits a luxury that few individuals could afford. Moreover, the COVID-19 outbreak has only made matters worse. Medical system inefficiencies may be resolved through broad adoption of automation and robotics automation systems. Bots with RPA capabilities represent a significant development in healthcare IT. With the knowledge, health practitioners can automate precisely, cut costs, optimize staff, and even implement dramatic changes. From the patient's perspective, AI algorithms can help people find the right doctor by precisely identifying their symptoms than conventional search engines.

Cognitive Automation:

It's indeed worth emphasizing cognitive automation as indispensable of the burgeoning healthcare technology trends. The most advanced drift towards true digital transformation is cognitive mechanization. The technical package and pertinency are now among the developing IT market trends in the healthcare sector, but they are about to fundamentally alter the way an industry is managed. Beyond the repetitious duties, it extends RPA's successes by replicating human behavior. It acts as the healthcare organization's digital brain, to put it briefly. In the interests of bringing decision acceleration into the market, Cognitive automation essentially uses the automated processes of current software vendors. In a matter of seconds, zettabytes of data may be processed, allowing for the delivery of suggestions to decision-makers that are ready for acceptance and supported by current data.  The eventual objective is to create a self-driving company with fully automated business operations. Not all healthcare payers today can afford such technologies. Yet, the potential for a single operating system and faster, more accurate decision-making make investment worthwhile. Cognitive automation will become more widespread and accessible to many members of the healthcare profession within a few years. As a key component of digitizing and modernizing its legacy systems, Merck Healthcare leverages the most recent medical technology from Cognitive automation from Aera Technology. For instance, the business was able to combine various ERP, manufacturing execution, and supply chain planning software types into a single solution.

Integration and Interconnectivity:

Since there was a lack of data integration throughout the worldwide pandemic, it became yet another healthcare technology trend. It has hindered carers' capacity to deliver the greatest care for years by slowing them down. It is commonly acknowledged that the openness and accessibility of medical devices are crucial components in assisting hospitals with better patient data flow, synchronization, and identification of high-risk patients more quickly and accurately, as well as with enhancing overall results. Nearly 59% of doctors, according to Google Cloud's research, think that improved interoperability will enable them to detect high-risk patients more rapidly. In contrast, 95% of physicians concur that improved interoperability will lead to better patient outcomes.

Conclusion:

An emerging area of research called "smart and intelligent healthcare" has caught the attention of academics, businesses, and governments from all over the world owing to its potential to turn the healthcare industry into a productive ecosystem. The work also offered an aerial perspective of the current COVID-19 pandemic in light of the created smart design solutions and classifications. Lockdowns and remaining at home aren't long-term options because it seems like COVID will be around to stick for a while. Tolerating the infection, though, might become the accepted norm.  In light of the increasing connectivity in human lives, a linked society with an advanced healthcare system appears to be the way of the future. The pandemic has significantly accelerated efforts to create a smart healthcare system and forced several countries to realign their priorities in order to inject more pervasive smartness into their operations in particular and in healthcare to battle COVID-19. Smart healthcare will assist in transforming reactive healthcare into preventative healthcare thanks to its benefits of enhanced care quality and accessibility for us all. Smart healthcare can make use of the data collected from various medical devices, mobile phones, tiny sensors, as well as other sources. Moreover, AI may empower people at the cloud or edge by offering insights, personalizing health services, and suggesting lifestyle and wellness improvements. Emerging technologies like IoT, AI, and telemedicine should really be assimilated into global and national public health sustainable growth and development as the globe transitions to digital healthcare. The main obstacles to adopting smart and intelligent healthcare are enhancing the technological proficiency of healthcare practitioners, public education, and health data exchanges while meeting privacy and security needs.

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Sathiyaraj

Dr. R. Sathiyaraj is currently working as an Assistant Professor in the GITAM School of Technology at the GITAM University, Bangalore Campus. He completed his Ph.D. at Anna University Chennai. His research interests lie in the area of Big Data Analytics, AI, and IoT. He has collaborated actively with researchers in several other disciplines of computer science, particularly traffic prediction systems and intelligent systems. Has more than 10 years of experience. He authored more than 25 publications and filed 5 patents.

Harvard Medical School - Leadership in Medicine Southeast Asia47th IHF World Hospital Congress