There’s never been a better time for the healthcare industry with emerging technologies transforming the industry and presenting exciting opportunities. The potential of Artificial Intelligence is vast. AI has the capability to perform tasks better than humans at a lower cost, reduced time, and increased efficiency. In fact, the use of AI in the healthcare industry is estimated to grow to $6.6 billion at a rate of 40% annually in 2021.
Moreover, reports suggest that AI and other technologies can help the healthcare industry save up to $100 billion annually through medicines and pharma. Technologies like AI and ML are offering better ways to identify diseases, treatment plans, conditions, screen health epidemics, efficiency in clinical trials, and medical research. AI is getting better at providing new ways of doing things. So, et’s have a look at how AI will transform healthcare in 2020.
What is the current usage of AI in Healthcare 2020?
Although 54% of professionals of the Healthcare IT services expect the widespread usage of AI in the industry by 2023. However, AI has already found multiple use cases in various segments of healthcare. In today’s time, 37% of healthcare organizations are leveraging AI for clinical applications within the organization. These tasks mostly include risk scoring, decision making, and safety warnings for medication. About 44% of the people use AI for operational tasks and 26% of people use AI to resolve financial problems.
How will AI transform Healthcare?
Early Detection Of Diseases
AI aids in detecting diseases such as cancer in the early stages and more accurately. Without the use of AI, the results of mammograms were not very accurate. As a result, 1 in 2 women was detected with cancer. However, with AI, mammograms result in 99% accuracy and 30% faster speed, thereby reducing the requirement of biopsies.
In 2020, AI in combination with wearables and other devices will help with early detection of diseases. For instance, the wearables monitor heart rate, calories, etc which can help in detecting early-stage heart diseases. This will aid doctors in treating the diseases at an early stage rather than having these diseases turn into life-threatening events.
Diagnosis & Treatment
Artificial Intelligence will aid healthcare professionals in better and accurate diagnosis and treatment. Moreover, doctors will be able to effectively monitor their patients remotely. For instance, Watson by IBM is facilitating the application of cognitive technology in healthcare organizations to gain access to large amounts of power diagnosis and health data. Watson has the capability to store and review huge amounts of medical information faster than human beings.
Further, AI will enhance the treatment approaches undertaken by healthcare professionals by managing diseases through a more comprehensive approach and helping patients follow their treatment programs. Additionally, surgical robots may completely reduce the work or replace surgeons during surgeries.
Maintaining Health
AI in combination with the Internet of Medical Things. It is helping people maintain their health and taking preventive measures through mobile applications. Health and fitness applications motivate people to maintain a healthy lifestyle and take control of their well-being. In 2020, AI will aid healthcare providers in understanding the daily health patterns and needs, to provide better guidance for maintaining health.
Better Decisions
Another way how AI will transform healthcare in 2020 is through better and more accurate decisions. Healthcare can be improved and diseases cured with timely and appropriate decisions. Predictive analysis can also improve clinical decisions and administrative tasks. For instance, pattern recognition aided by Artificial Intelligence can help identify the development of a certain condition in a patient or the health deterioration due to factors such as genomics, lifestyle or environment. Therefore, with predictive care, AI will be able to anticipate chronic diseases at an early stage and suggest preventive measures.
Better Outcomes For Cancer Patients
AI is finding its way into assisting researchers with the diagnosis and management of cancer. As per these researchers, AI was used in developing a system that is able to identify different types of cancer cells with a 98% accuracy. Further, researchers also built machine learning ( a subset of artificial intelligence) model that stimulates cancer cell’s metabolism to examine the effects of different drugs on curbing cancer development. They created models of cancerous and healthy cells digitally and incorporated the genetic data from 10,000 patients. With this system, the researchers identified drugs that stop the growth of cancer cells.
Research & Training
One of the challenges the healthcare industry faces, is the time taken by drugs to reach patients from the research lab. Presently, as per the California Biomedical Research Association, the drug reaches the patient in an average of 12 years. Only 1 in 5 drugs out of the 5000 that reach human testing after preclinical testing, receives approval for usage by humans. It costs almost $359 million to develop and market a drug from the lab to the patient. Applying AI in drug research and development process can significantly reduce time and costs to market drugs.
AI will also enhance the training techniques through simulations that are incomparable with computer-driven algorithms. It will facilitate training through smartphones anywhere and at any time.
Conclusion
Experts are still uncertain about the existing possibilities and future potential of AI. However, AI creates a big hype in the healthcare industry. AI is yet to gain the acceptance and trust of medical professionals who use traditional methods which poses a major challenge for the implementation of AI in healthcare. The aim of implementing AI in the healthcare industry is to improve the accuracy and reduce the complexity of tasks, and not to replace the healthcare providers. How AI will transform healthcare in 2020 is yet to be experienced with improved healthcare facilities, better diagnosis and reduced costs.
