Artificial intelligence (AI) is being applied across the healthcare spectrum — from administration to patient interaction and medical research, diagnosis and treatment.
What is healthcare AI?
Healthcare AI is the application of artificial intelligence to medical services and the administration or delivery of medical services. Machine learning (ML), large and often unstructured datasets, advanced sensors, natural language processing (NLP) and robotics are all being used in a growing number of healthcare sectors.
Along with great promise, the technology offers significant potential concerns — including the abuse that can come from the centralization and digitalization of patient data as well as possible linkages with nanomedicine or universal biometric IDs. Equity and bias have both also been concerns in some early AI applications, but the technology may also be able to improve healthcare equity.
Although deployment of AI in the healthcare sector has truly just begun, it is becoming more commonly used. Gartner pegged 2021 global healthcare IT spending at $140 billion, with enterprises listing AI and robotic process automation (RPA) as their lead spending priorities.
Healthcare costs approached a fifth (19.7%) of the total U.S. economy in 2020 (an estimated 19.7% or $4.1 trillion). Over half of that spending, for the first time, was racked up by the government, where fraud is especially high.
Thus, the potential value of healthcare AI, from administration to medical AI is vast.
10 top applications of artificial intelligence in healthcare in 2022
Here are 10 of the top areas where healthcare AI use cases are being developed and deployed today.
1. Healthcare administration
Administrative expenses are estimated to comprise 15% to 25% of total healthcare costs. Tools to improve and streamline administration are valuable for insurers, payers and providers alike.
Identifying and cutting down fraud, however, may provide the most immediate return as ealthcare fraud can happen on many levels and be committed by various parties. In some of the worst cases, fraud may cause insurers to get billed for services not rendered or result in surgeons performing unnecessary operations to get higher insurance payments. Insurers may also get billed for defective devices or test kits.
AI can be a useful tool in stopping fraud before it happens. Just as banks commonly use algorithms to detect unusual transactions, and health insurers can do the same..
2. Public health
AI is already being applied across the public health sector. Including
3. Medical research
The applications for AI in medical research are also expansive. Examples range from new and repurposed drug discovery to clinical trials, including:
4. Medical training
AI may also alter how medical school students receive parts of their education. Including in cases like the following:
5. Medical professional support
AI is also deployed to support medical professionals in clinical settings, including the following:
6. Patient engagement
AI is also deployed to support patients directly:
7. Remote medicine
Telemedicine in the form of virtual doctor visits have become increasingly common since the COVID-19 lockdowns. In addition to those, AI is supporting other forms of remote medicine as well, including:
8. Diagnostics
AI is also utilized for healthcare center diagnostics, including by:
9. Surgery
AI does not eliminate surgical issues, but it can potentially reduce them while enhancing outcomes for patients and surgeons alike. This is illustrated in the following examples
10. Hospital care
Along with the above-described diagnostic use cases, clinicians also must meet patients physical needs and, more prosaically, stock supplies and deliver goods. AI-powered collaborative robots are starting to ease the burden. Gartner expects 50% of U.S. providers to invest in robotics process automation (RPA) by 2023. Some examples of RPA in hospitals include:
Atheon provides robots that support not only medical functions, but tasks such as linen distribution and waste removal.