Artificial Intelligence: Redefining Roles in Healthcare
Mobile platforms that convert patient interactions into clinician notes in seconds1. Algorithms that cut research and development (R&D) timelines from years to months2. Robots that deliver food and clean up after patients3.
In an industry grappling with persistent manpower challenges, artificial intelligence (AI) and other emerging technologies are stepping up with transformative solutions — and they are proving to be vital game-changers in reshaping healthcare.
Whether or not you work in healthcare, the industry’s manpower crunch is clear to everyone. Japan estimates it will have a shortage of 337,000 care workers by 20255. China only has 1 million care workers in employment despite a need for 13 million2. There are only about 22 medical specialists for every 100,000 residents in Indonesia1. Singapore needs at least 24,000 more healthcare staff by 20306.
And this isn’t just a regional problem. As the Organisation for Economic Co-operation and Development (OECD) warns, global long-term care labour shortages could soon reach “unacceptable levels” if no decisive action is taken7.
One solution? AI.
From efficient administrative assistants to powerful assets in medical imaging, diagnosis, and drug discovery, AI is quickly becoming a mainstay in healthcare.
In fact, the AI healthcare market is projected to soar from USD 11 billion in 2021 to USD 188 billion by 20308, with generative AI poised to unlock USD 1 trillion worth of potential improvements9. It’s no surprise that nearly half of healthcare providers in Asia Pacific are considering its use to ‘augment clinician efficiency’ and ‘redefine patient experiences’10.
Clearly, AI is doing something right.
And as its presence grows in the industry, what additional roles will it assume? How will it collaborate with and augment our workforce?
Let’s explore.
With advanced intelligence and automation capabilities, AI can serve as excellent assistants to offload routine tasks from healthcare professionals and keep a watchful eye on patients 24/7.
Smart video analytics can transform surveillance cameras into proactive, round-the-clock assistants, enabling them to detect falls and identify absconding patients before promptly alerting healthcare professionals for immediate action.
In private areas, technologies like scream detection and LiDAR will step in to ensure that patient safety is never compromised.
Video analytics can also be used in operating theatres to account for all surgical instruments before and after a surgery. This reduces the risk of accidental retention and ensures the integrity of surgical procedures. In all cases, robust privacy features will be in place to protect the confidentiality of staff and patients.
AI chat assistants are taking over tasks like sending medical reminders, managing schedules, and routinely checking in on patients, allowing healthcare professionals to concentrate on cases that truly require their attention11.
The proliferation of the Internet of Medical Things (IoMT) allows healthcare professionals to better track, understand, and predict their patients' conditions and needs, while at the same time, empowering individuals to manage their health more proactively12.
When paired with intelligent video analytics and face recognition technology, surveillance cameras can become formidable round-the-clock security systems that keep facilities safe by:
One of AI’s biggest strengths is its ability to analyse large volumes of data in seconds, making it an invaluable tool in supporting drug research[1]and clinical decision-making.
Canon’s Automation Platform, for example, is a zero-click, deep learning solution that processes and delivers medical images directly from scanners to clinical decision-makers. This creates a new clinical workflow that accelerates triaging, worklist prioritisation, and treatment decisions.
Advanced intelligent Clear-IQ Engine (AiCE) is the world’s first AI-assisted MR and CT deep learning reconstruction technology. It harnesses the computational power of Deep Convolutional Neural Networks (DCNN) to reduce noise and enhance signal clarity, delivering sharp, clear, and distinct images quickly.
From AI to generative AI, machine learning, neural networks, deep learning, and more, the role of AI in healthcare is only going to expand as technology evolves.
While the exact ways technology will reshape healthcare are still unfolding, one thing’s for sure: the more capable technology becomes, the more it empowers us to do what we do best — being human.
And that’s what healthcare truly needs, isn’t it?
Reshape the future of healthcare with Canon today.