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Growing Applications of Artificial Intelligence in Healthcare
Published
05th Sep, 2023
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Artificial intelligence (AI) deals with building smart devices/machines that are capable of performing tasks without the presence of human intelligence, autonomously. Globally, it’s one of the most popular new-age skills today with a wide range of applications across sectors like finance, healthcare, space exploration and manufacturing.
AI-driven Healthcare market
According to a report by MarketsandMarkets, AI in healthcare domain is projected to reach USD 36.15 billion by 2025. There’s a growing need for lowering healthcare-related costs, processing large amounts of data, widespread adoption of precision medicine, as well as a dip in hardware costs in this domain.
According to a recent report, there would be 58 million AI jobs by 2022. Researchers Frost & Sullivan claimed in their study that about $6.7 billion will be generated globally using artificial intelligence systems in healthcare by 2021. Hence, the demand for professionals trained in AI with expertise in healthcare is on the rise.
Below are some applications of AI in healthcare:
AI-based diagnostic technology
Disease diagnosis is the most integral part of healthcare. Accuracy in diagnosis is imperative to the right treatment plan. According to a recent Harvard Medical Practice study, faulty diagnosis accounted for 17% of preventable errors among hospitalized patients. This is where the accuracy and sophistication of AI will come handy. AI-supported diagnostic machines are being increasingly used in hospitals today. Their ability to analyze large amounts of data from medical images has paved the way for early diagnosis of diseases. Early diagnosis of cancer, stroke, heart attack and tumors can help doctors develop an exhaustive treatment plan for patients before the disease progresses.
AI and Machine Learning have been commonly employed to detect the following conditions:
- Lung cancer and strokes
- Heart diseases and its severity
- Skin lesions and its classification
- Diabetic retinopathy
AI-Powered Biomarkers
Conventional medicine used to follow the ethos ‘one-size-fits-all’. However, precision medicine advocates that diagnosis of certain diseases and medicines for a patient varies according to their genetic makeup, lifestyle and environmental influences. This is where biomarkers based on AI have a role to play. These markers are intelligent enough to track real-time audio/visual information on a patient’s vital health parameters. Eventually, doctors can take a look at the data collected and devise a comprehensive treatment plan exclusive to the patient.
Virtual nursing assistance and remote monitoring
Nurses and other healthcare assistants are the backbones of any healthcare network. AI-based virtual assistants and chatbots provide support to these care providers by reducing their workload. Specifically, AI-based virtual assistants aid in monitoring patients post-discharge and making a lot of outpatient services hassle-free.
AI-enabled wearable devices serve as virtual health assistants that remind patients to follow their diet/medicine chart. Round-the-clock remote monitoring of their vital signs sends real-time alerts to care providers too. This AI-based tracking approach prevents unnecessary visits to the physician as well.
AI-based drug discovery
In the United States, only 5 in 5000 drugs undergo the process from preclinical testing to human testing. The chance of a new drug to reach the market is just 1 in 5000!
When AI-driven computing is applied to drug testing and research, there is a greater degree of accuracy. The route of drug discovery (from testing to market availability) also becomes faster and more cost-efficient. Many pharmaceutical companies have adopted AI-based drug discovery to develop drugs that could support the treatment of cancer and other chronic diseases.
AI-enabled hospital care
For patients suffering from chronic diseases or even acute conditions, AI can help a great deal in simplifying care delivery. Procedures like the monitoring of IV solutions, tracking the patient’s medications, patient alert/feedback systems, performance assessment systems and patient movement tracking within hospitals can be managed with AI assistance. Robot-assisted surgeries are highly accurate, and have an added advantage of reducing human error.
A 2017 report by Accenture claimed that AI-assisted clinical health applications could help save a whopping $40 billion dollars in robot-assisted surgery and $18 billion in administrative workflow assistance.
AI is here to stay
Despite the presence of AI applications in healthcare for many years, they still have a long way to go. However, one of the major challenges faced in AI-based healthcare is the lack of skilled AI-experts with domain knowledge in life sciences.
Exciting opportunities for trained AI professionals
The industry is growing rapidly at a pace of 40% per year. However, there is a dire shortage of professionals with fewer than 10,000 professionals with the right skills to create fully functional artificial intelligence systems. Aspiring AI engineers thus have a plethora of opportunities to redefine healthcare as well as land exciting job roles.
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