A man in his 60s appeared at a private hospital in Klan Valley last year for a routine health check. Despite being a smoker, he showed no symptoms that could indicate health problems.
That day he received chest x-rays, augmented by artificial intelligence (AI) software. It is designed to detect subtle anomalies that the human eye can sometimes overlook.
Professor Anand Sachisanandan, consultant cardiothoracic surgeon, recalls how the software detected a small shadow in the upper zone of the male left lung.
“It was something that could easily be overlooked or overlooked by traditional x-ray imaging,” he said in a statement. Lifestyletech.
Professor Anand added that further investigation revealed elevated tumor markers. This may be a sign of cancer in the body. This may sound surprising, but additional testing is required to confirm the diagnosis.
“He was quickly investigated with a CT chest scan, a PET scan and a biopsy. He confirmed early stage primary lung cancer,” he says.
Professor Anand added that he had performed surgery to remove (removal) the tumor. Three days later, the man recovered well and went home.
AI can sift through vast amounts of data very quickly, paving the way for future precision diagnosis and personalized treatments. – Professor Anand Sachithanandan
This is the first known case of AI to help detect lung cancer in Malaysia, and Professor Anand says the technology has cloud-based Qure.AI software equipped with deep learning algorithms.
“This case demonstrated the potential for screening lung cancer with chest x-rays and how the technology can help radiologists.
“It also highlighted the fast turnaround time that contributed in part to the patient's completion of decisive treatment within two weeks,” he adds.
AI and early detection
Malaysia began incorporating AI screening in 2020. This is when private health centers launched an initiative to use AI to detect retinal diseases. The adoption of AI is currently expanding to public health care, promoting initiatives that promote the Ministry of Health to use AI to detect diseases.
Last year, the Ministry of Health announced the deployment of Dr. MATA, an AI-driven software solution for detecting and diagnosing diabetic retinopathy, an eye disease caused by diabetes, in a pilot project that includes around 140 government clinics.
According to a report by Deputy Director of Research and Technical Support, Datuk Dr nor Fariza Ngah, the technology can help generate eye test results at a faster rate, leading to better results for patients.
Then, in May, the Ministry of Health announced that starting this year, AI-powered lung cancer screening initiatives will be rolled out at seven health clinics across the country, including Kelantan, Pahan and Keda.
“This AI capability will significantly improve incident detection rates,” Bernama said Dr. Datuk Seri, Dr. Dzulkefly Ahmad, during the National Lung Health Initiative 2025-2030 briefing in May.
Professor Anand states that lung cancer is one of Malaysia's leading cancers, with an increase in reported cases, based on the latest National Cancer Registry Report (2017-2021).
He adds that the Ministry of Health's initiative to prioritize screening for lung cancer is timely.
“Because the Ministry of Health remains the largest healthcare service provider, adoption of AI-enabled screenings in government clinics could have a significant impact on meaningful stage shifts, in order to detect more cases at more stages, if cancer is suitable for curative treatments like surgery,” he adds.
While AI can be expanded and deployed to rural areas, allowing radiologists and physicians to assist clinic staff on-site, Professor Anand points out that a strong communication network is essential for effective functioning. – Images by Freepik
Professor Yong Chai Hong of the School of Medicine at Taylor University School of Medicine, School of Health Sciences, says AI-driven diagnostic screening at government clinics reflects the national agenda of the transition to preventive data-driven healthcare.
“This effort can also be seen as an attempt to demonstrate Malaysia's commitment to bridge the healthcare gap between urban and rural communities through scalable, data-driven solutions.
“It illustrates the transition from reactive to aggressive care, where early detection could lead to timely interventions, improved outcomes, and reduced burden on advanced health facilities,” Professor Yeong said in a statement to Lifestyletech.
Professor Anand says that AI is ubiquitous and its impact is now visible in all areas of people's personal and professional life.
“The government has recognized the possibilities and has been actively working to adopt a variety of innovative, AI-driven programs early,” he adds.
He also believes that social media has helped normalize the broader concept of AI that “it appears to be less difficult and more accepting” for most people.
He added that there is also an increase in scientific evidence pointing to AI improving diagnostic accuracy and enhancing accuracy and personalized healthcare delivery. “Collectively, this may have contributed to wider acceptance.”
Handling data
Despite this possibility, the use of AI in disease detection still has some limitations that need to be addressed, Professor Yong says.
AI should remain a support tool, but clinicians must continue to play a central role in decision-making. – Professor Yong Chai Hong
“One of the main concerns is algorithm bias. Many AI models are trained on datasets of specific populations, which may not be well generalized to Malaysia's diverse demographic environment without appropriate local validation,” she explains.
She also warns that there is a risk of overreliance on AI output, which may undermine clinical judgment if not managed carefully.
“AI needs to remain a support tool, but clinicians must continue to play a central role in decision-making, which ensures patient safety and maintains professional accountability,” she says.
Another important issue lies in data governance. Professor Yong emphasizes that the safe, ethical and transparent use of patient data requires a strong regulatory framework to protect privacy, ensure security and build public trust in AI-powered health systems.
To ensure the responsible ethical use of AI in the public health sector, she calls for a multifaceted approach that supports it based on clear regulatory oversight and clear standards.
“Authors such as the Ministry of Health need to establish national guidelines for managing the validation, certification, and post-residency surveillance of AI tools in a clinical setting,” she says.
She adds that robust measures are needed to protect data privacy and promote transparency.
“This includes building a secure digital infrastructure, ensuring that AI models, particularly regarding the origin and representation of the dataset used, are tested with development, training, and full transparency.”
She also highlights the need for continuous surveillance.
“AI tools need to be evaluated and updated regularly to remain accurate in real-world conditions, properly tuned, and not produce unequal results in different patient groups, particularly in today's rapidly evolving healthcare environment.”
While AI can be expanded and deployed to rural areas, allowing radiologists and physicians to assist clinic staff on-site, Professor Anand points out that a strong communication network is essential for effective functioning.
“The cost of installing software along with maintaining and upgrading server networks such as 5G infrastructure can be a limiting factor,” he adds.
Dzulkefly said in a report from Bernama that its cost to deploy AI lung screening at selected government clinics is relatively modest, with only RM70,000, which is worth investing in the benefits of early disease detection.
“I hope carefully.”
As the founder of the Non-Governmental Organization Lung Cancer Network Malaysia (LCNM), Professor Anand has become an important advocate for the use of AI in lung cancer screening. In 2021, LCNM launched a free screening initiative using AI-enhanced chest x-rays at a health clinic in Klang Valley, reaching over 10,000 participants.
“I am excited and cautiously hopeful about the wider adoption of AI screening,” he says.
He says that he is now ripe for a national-level lung screening program, as most cases were detected late, with the burden of disease and poor outcomes. He adds that other countries, such as the UK, have launched national-level lung screening programs in 2019, and Australia is about to launch an initiative in July.
Ultimately, Professor Anand explains that screening is not a one-off test, but rather a part of a lengthy process that involves follow-up scans, biopsies and treatment, requiring proper funding and labor planning.
“There must be a well-tuned pathway for those with abnormal findings to follow up and be investigated further immediately by AI-enabled chest x-rays,” he adds.
For AI tools to be effectively integrated into public health, Professor Yeong says the digital infrastructure of hospitals, clinics and screening centres needs to be strengthened.
“This includes expanding the electronic health record (EHR) system, protecting the storage of medical data, and improving network connectivity, particularly in rural and underserved areas where digital access may be restricted,” she adds.
They also need to provide medical professionals with essential knowledge of digital literacy training and data science.
She also says there should be a structured pathway to expanding and expanding successful pilot projects into “sustainable, national AI-powered programs.”
Beyond health screening
Professor Yong said the possibilities for AI-driven solutions in the public sector in Malaysia are enormous. Beyond screening, she believes that AI plays an important role in patient management using tools such as AskCPG.
“By providing real-time recommendations based on patient data, it helps streamline the implementation of the National Clinical Practice Guidelines (CPGS) and optimize healthcare workflows,” she adds.
For hospital operations, she says that AI will also help optimize management workflows by predicting patient volume, managing bed occupancy and even automating booking scheduling.
“Beyond clinical care, AI is increasingly used in drug discovery and clinical trials. It allows for optimizing drug design tailored to a specific population or individual, accelerates the identification of new drug candidates, and matches patients with appropriate clinical trials based on eligibility criteria,” she adds.
Professor Anand also sees the potential for AI to shape the future of health screening in Malaysia.
“AIs have the potential to sift through vast amounts of data very quickly, paving the way for future precision diagnosis and personalized treatment,” he said, adding that AI could predict and detect early warning signs for chest x-rays or CT scans.
Early interventions can significantly improve the patient's survival potential, but recovery also depends on the individual's own commitment to his or her health.
Professor Anand says that a man in his 60s who was diagnosed with lung cancer through AI-assisted screening last year needs regular follow-up for the next three to five years.
“He completed postoperative adjuvant chemotherapy (according to international protocols), but thankfully remains cancer-free. His previously elevated tumor marker levels have normalised. He has also stopped smoking!”
