Artificial intelligence is being used in healthcare for everything from answering patient questions to assisting with surgeries and developing new pharmaceuticals.
According to Statista, the artificial intelligence (AI) healthcare market, valued at $11 billion in 2021, is projected to be worth $187 billion in 2030. That massive increase means we will likely continue to see considerable changes in how medical providers, hospitals, pharmaceutical and biotechnology companies, and others in the healthcare industry operate.
Better machine learning (ML) algorithms, more access to data, cheaper hardware and the availability of 5G have contributed to the increasing application of AI in the healthcare industry, accelerating the pace of change. AI and ML technologies can sift through enormous volumes of health data—from health records and clinical studies to genetic information—and analyze it much faster than humans.
As health and fitness monitors become more popular and more people use apps that track and analyze details about their health, they can share these real-time data sets with their doctors to monitor health issues and provide alerts in case of problems.
AI solutions—such as big data applications, machine learning algorithms and deep learning algorithms—could also be used to help humans analyze large data sets to assist in clinical and other decision-making. AI could also be used to help detect and track infectious diseases, such as COVID-19, tuberculosis and malaria.
One benefit the use of AI brings to health systems is making gathering and sharing information easier. AI can help providers keep track of patient data more efficiently.
One example is diabetes. According to the Centers for Disease Control and Prevention, 10% of the US population has diabetes. Patients can now use wearable and other monitoring devices that provide feedback about their glucose levels to themselves and their medical team. AI can help providers gather that information, store and analyze it, and provide data-driven insights from vast numbers of people. Leveraging this information can help healthcare professionals determine how to better treat and manage diseases.
Organizations are also starting to use AI to help improve drug safety. The company SELTA SQUARE, for example, is innovating the pharmacovigilance (PV) process, a legally mandated discipline for detecting and reporting adverse effects from drugs, then assessing, understanding and preventing those effects. PV demands significant effort and diligence from pharma producers because it’s performed from the clinical trials phase all the way through the drug’s lifetime availability. Selta Square uses a combination of AI and automation to make the PV process faster and more accurate, which helps make medicines safer for people worldwide.
In some cases, AI could reduce the need to test potential drug compounds physically, which is an enormous cost-savings. High-fidelity molecular simulations can run on computers without incurring the high costs of traditional discovery methods.
AI also has the potential to help humans predict toxicity, bioactivity, and other characteristics of molecules or create previously unknown drug molecules from scratch.
As AI becomes more important in healthcare delivery and more AI medical applications are developed, ethical and regulatory governance must be established. Issues that raise concern include the possibility of bias, lack of transparency, privacy concerns regarding data used for training AI models, and safety and liability issues.
“AI governance is necessary, especially for clinical applications of the technology,” said Laura Craft, VP Analyst at Gartner. “However, because new AI techniques are largely new territory for most [health delivery organizations], there is a lack of common rules, processes and guidelines for eager entrepreneurs to follow as they design their pilots.”
The World Health Organization (WHO) spent 18 months deliberating with leading experts in ethics, digital technology, law and human rights and various Ministries of Health members to produce a report called Ethics & Governance of Artificial Intelligence for Health. This report identifies ethical challenges to using AI in healthcare, identifies risks, and outlines six consensus principles to ensure AI works for the public’s benefit:
The WHO report also provides recommendations that ensure governing AI for healthcare both maximizes the technology’s promise and holds healthcare workers accountable and responsive to the communities and people they work with.
AI provides opportunities to help reduce human error, assist medical professionals and staff, and provide patient services 24/7. As AI tools continue to develop, there is potential to use AI even more in reading medical images, X-rays and scans, diagnosing medical problems and creating treatment plans.
AI applications will continue to help streamline various tasks, from answering phones to analyzing population health trends (and, likely, applications yet to be considered). For instance, future AI tools may automate or augment more of the work of clinicians and staff members. That will free up humans to spend more time on more effective and compassionate face-to-face professional care.
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