National University Health System Pte, Ltd.

While AI can offer immense potential to improve patient outcomes and streamline medical processes, system flaws can pose risks to ethics, security and data accuracy. Dr Gao Yujia, assistant group CTO of the National University Health System, urged caution in AI implementation in healthcare in the keynote session, "Unveiling the Dark Side of AI," at HIMSS24 APAC . "While AI has undoubtedly enhanced patient care, it's crucial to acknowledge the potential pitfalls," he emphasised. A primary concern is the risk of bias in AI algorithms. Dr Gao cited an incident during COVID-19 where an AI algorithm, trained on biased data, disproportionately down-prioritised people of colour who had the same conditions as other patients. It is critical, Dr Gao stressed, that AI systems are trained on diverse and representative datasets. "Similar to a 'garbage in, garbage out' scenario, AI can only be as accurate as the data that is fed to it. Some AI algorithms fail to perform as expected because they were not trained on relevant data or were overfitted to specific datasets." Beyond data quality, Dr Gao also raised concerns about the ethical implications of AI in healthcare. "We use AI to help us organise our thoughts, but that same intent can be used maliciously. For example, AI-generated deepfakes have been used to impersonate healthcare workers for ransomware attacks. Fraudulent medical research is also a possibility because of how convincing AI-generated content can be." Asked if all is "doom and gloom" for AI in healthcare, Dr Gao disagreed. "A more immersive and instantaneous digital world is inevitable, but what protects us [from AI risks] is maintaining a balance between human agency and AI's utility." According to Dr Gao, ethical frameworks, transparency and human oversight are key factors in harnessing the power of AI while mitigating its potential harms. He advised healthcare professionals to neither fear AI nor be fearless of AI. "We should take a step back to understand, appreciate, understand and plan how to integrate AI into healthcare in our society."

Organisational readiness, prevailing regulations, and user understanding are some factors that impact the success of AI deployment in health systems. During the HIMSS24 APAC panel session, "AI Horizons: Exploring the Future of Innovations," Professor In-Young Choi, vice CIO of Catholic Medical Centre (CMC), Dr Shankar Sridharan, chief clinical information officer at Great Ormond Street Hospital, and Dr Ngai Tseung Cheung, the head of Information Technology and Health Informatics at Hospital Authority, Hong Kong (HAHK), shared outcomes, lessons, and anticipation of AI implementation in healthcare. Professor Kee Yuan Ngiam, head of the AI office at the National University Health System, moderated the panel. The realities of AI implementation AI in healthcare has been touted as an all-in-one solution for digital needs, but Dr Cheung thinks otherwise. "AI is an amazing technology and sometimes appears magical, but it really isn’t. AI is a tool no different from any other technology we can put in play." He shared questions to consider when applying AI: "How does AI get put into a workflow at scale so that it can deliver positive outcomes? What is the impact [of AI on the organisation]? How does it affect the users? Does the output give you something actionable?" Dr Shankar of Great Ormond Street Hospital shared these preliminary perspectives. "The medicinal asset [for implementing AI] is enthusiasm, which can be quite infectious. But we need to address its purpose... When we do a benefits assessment on safety, security and technology, is there a clinical, operational or patient experience benefit?" Prof Choi, however, held a different view, given the strict regulatory environment she is working with. "We do not have government-based control for EMR contracts. Each hospital has its own [exclusive] data. It is not easy to share data with other hospitals, and it is not easy for AI companies to access hospital data. If the [AI] algorithm uses cloud computing, it will be outside Korea, and the law does not allow our medical data to enter foreign countries," she elaborated. Overcoming barriers to adoption Given its multi-layered nature, the deployment of AI tools may require additional reassurance. Dr Cheung shared HAHK's proactive stance in conducting internal validations of AI tools. In contrast, Dr Shankar provided data safety reassurance through vetted partnerships. "We have a trusted research department and commercial relationships with pharma and industry that airlock [data]. Then, we communicate to our CEO that our data is safe and that the [AI] tool is useful and valuable without losing data due to risks." Dr Cheung also noted that regular demonstrations can appease pessimism levels among health staff. "Good thing is we have 43 hospitals. If it (an AI test) does not work out, it is fine. Then we can show that we tried... If we can show them that it works and the hesitant [staff and doctors] switch [to optimism], that will be good... We have to show them that the AI is okay [for use]." Realising future AI potential Despite adoption barriers, CMC has software development plans which could help pathologists perform treatment for lung cancer. "One patient can have many subtypes of cancer. For example, an individual can have a 20% capillary subtype. Humans can’t count that [figure], but AI can. It can help clinicians provide better treatment to the patients," Prof Choi explained. "We focus on one specific disease for now. But after generative AI comes, maybe AI can see [relevant health] details in a more comprehensive way.” Meanwhile, Dr Cheung contested the human impact of future AI. "Today's AI is not sentient. It is not at the level of a human being. However, there is a concept of artificial general intelligence that is touted to be superhuman. If that [technology] is better than humans in every way, there will be a massive change to medicine and humanity." Dr Shankar believes that there is a long way to go in realising AI's full potential. "We are a bit like cavemen [with AI'. Our limitations are our own, as are our use cases."

National University Hospital unveils spine AI National University Hospital has introduced an AI tool to analyse lumbar spinal stenosis, a common indication for surgery among senior patients. According to a media release, the tool called Spine AI automatically detects areas of narrowing of spinal canal and categorises them by severity. It was trained using more than 18,000 lumbar spine MRI images of 446 patients. In a study, the technology took as fast as "47 seconds" to analyse each spine. Lumbar spinal stenosis is a condition in which the spinal canal narrows in the lower back and compresses the nerves and blood vessels supplying the lower limbs. Currently being evaluated across the NUHS radiology department, Spine AI was developed by NUH, together with NUS School of Computing and the National University Spine Institute. Siemens Healthineers was also tapped to help optimise the AI's user interface. NUH is said to generate around 4,00 lumbar MRI scans each year. With Spine AI automating its analysis in seven minutes per scan on average, it could deliver 466 hours in time savings per year, estimates Dr Andrew Makmur, NUHS Group CTO and a consultant of the NUH Department of Diagnostic Imaging. Korea to deploy AI to check on independent living seniors The South Korean Ministry of Health and Welfare and the Comprehensive Support Center for the Elderly Living Alone will be utilising AI to connect with about 42,000 senior citizens expected to spend the upcoming Chuseok holidays alone. Chuseok is a major autumn harvest festival in the Korean peninsula. In South Korea, it is celebrated for three days. A part of the government's personalised elderly care service, the AI Call service utilises text-to-speech and speech-to-text technology to make voice calls and collect and transmit call information. Meanwhile, SK Telecom and Lotte Welfare Foundation have been tapped to provide technical assistance for the holiday call service. Thai regional hospital trials CXR AI Phrapokklao Hospital, a major regional hospital in Chanthaburi, a province south-west of Thailand's capital Bangkok, has recently implemented a chest X-ray (CXR) analysis AI to augment community screening of lung cancer. "In most Thai government hospitals, [CXRs] are interpreted by non-radiologists. However, in community hospitals, there are often no radiologists available to read CXRs at all. By overlaying specialist AI to read all cases, we can support clinicians in detecting incidental high-risk nodules that may lead to lung cancer," Dr Passakorn Wanchaijiraboon, deputy director of Phrapokklao Hospital’s Cancer Centre of Excellence, was quoted as saying. He led a recent evaluation study of the CXR solution qXR by the Indian company Qure.ai. "The implementation of CXR AI is particularly beneficial in the context of community hospitals, where it can significantly enhance diagnostic capabilities in the absence of on-site radiologists," Dr Wanchaijiraboon, who is also an oncologist, added. Early this year, Qure.ai received the US Food and Drug Administration approval for the lung nodule on the qXR range of CXR analysis solutions.