Latest news with #JoeYeong
Arab Times
a day ago
- Health
- Arab Times
AI-powered model to predict liver cancer recurrence
SINGAPORE, July 22, (Xinhua): Singaporean researchers have developed an artificial intelligence-powered scoring system capable of predicting the recurrence of liver cancer, according to a press release from the Agency for Science, Technology and Research on Monday. Developed by scientists from the Institute of Molecular and Cell Biology (IMCB) under the agency in collaboration with the Singapore General Hospital, the system can forecast the recurrence of hepatocellular carcinoma, the most common type of liver cancer, with approximately 82 percent accuracy. The system works by analyzing the spatial distribution of natural killer immune cells and five key genes within liver tumor tissues. "In Singapore, up to 70 percent of liver cancer patients experience recurrence within five years," said Principal Investigator Joe Yeong from the IMCB, noting that this system empowers clinicians to intervene as early as possible. Researchers validated the system using tissue samples from 231 patients across five hospitals. It is now accessible via a free web portal for research purposes, with plans underway to integrate it into standard clinical workflows.
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Business Standard
a day ago
- Health
- Business Standard
Scientists develop AI system that can predict liver cancer recurrence
In a major medical breakthrough, scientists in Singapore have developed an AI-powered diagnostic tool capable of accurately predicting the recurrence of liver cancer — specifically hepatocellular carcinoma (HCC), one of the deadliest cancers globally. The Tumour Immune Microenvironment Spatial (TIMES) score, an innovative diagnostic system, has been developed through a joint effort by researchers at the Agency for Science, Technology and Research (A*STAR)'s Institute of Molecular and Cell Biology (IMCB) and Singapore General Hospital (SGH), according to a press release from SGH. The TIMES model, which was recently featured on the cover of the renowned journal Nature, is being seen as a game-changer in personalised cancer diagnostics and early intervention. What is hepatocellular carcinoma? Hepatocellular carcinoma (HCC) is the most common type of liver cancer, often linked to chronic liver diseases such as cirrhosis. It remains the third leading cause of cancer-related deaths worldwide, and recurrence rates are alarmingly high. In Singapore alone, around 70 per cent of liver cancer patients experience a relapse within five years of treatment, making early detection of the recurrence vital for improving survival rates. How the TIMES system works The TIMES score uses advanced machine learning and spatial biology to assess the likelihood of liver cancer returning after surgery. By integrating multiplex immunofluorescence imaging, spatial transcriptomics, and proteomics data, the model uses the XGBoost machine learning algorithm to detect molecular patterns within tumour tissue—patterns that traditional diagnostic methods cannot identify. Specifically, it evaluates the distribution of natural killer (NK) cells and the expression of five key genes inside the tumour microenvironment. This combination allows the AI to determine a patient's risk of recurrence with approximately 82 per cent accuracy, outperforming existing clinical tools. Potential of the TIMES system Early and accurate prediction of relapse means that doctors can tailor follow-ups and treatment plans more effectively. This would increase the chances of long-term survival. According to Dr Joe Yeong, Principal Investigator at A*STAR IMCB and SGH's Department of Anatomical Pathology, the TIMES system represents a big leap in the ability to anticipate cancer relapse and initiate timely intervention. The study also identified a biomarker called SPON2, produced by NK cells. SPON2 has been found to be associated with the risk of recurrence. Studies have further revealed that SPON2 and NK cells enhance anti-tumour activity by improving migration towards cancer cells and activating CD8 and T-cells. This finding could also pave the way for improved AI-guided immunotherapy. Denise Goh, co-first author and senior research officer at A*STAR IMCB, explained, 'TIMES turns standard pathology slides into predictive diagnostic tools. Not only does the AI algorithm improve prognostic precision, but it also enables clinicians to revise treatment and monitoring plans proactively — potentially saving lives.' Validated and ready for wider use The TIMES model was tested using tumour samples from 231 patients across five hospitals, demonstrating its reliability across diverse datasets. To encourage global collaboration, the team has also launched a free online portal that allows medical professionals to upload tissue images and get AI-generated recurrence risk assessments. The underlying software framework has been patented, and further validation trials are scheduled at SGH and the National Cancer Centre Singapore later this year. The research team is currently working with diagnostic partners to standardise the system and transform it into a clinically approved diagnostic kit for routine hospital use. SGH, Singapore's largest tertiary healthcare institution and a globally recognised academic medical centre, played a key role in this project and will continue to support its clinical rollout. If successful, the TIMES score could become a key breakthrough for future cancer care.
United News of India
2 days ago
- Health
- United News of India
Singapore researchers develop AI-based model to predict liver cancer recurrence
Singapore, July 21 (UNI) Singaporean researchers have developed an artificial intelligence-powered scoring system capable of predicting the recurrence of liver cancer, according to a press release from the Agency for Science, Technology and Research on Monday. Developed by scientists from the Institute of Molecular and Cell Biology (IMCB) under the agency in collaboration with the Singapore General Hospital, the system can forecast the recurrence of hepatocellular carcinoma, the most common type of liver cancer, with approximately 82 per cent accuracy. The system works by analyzing the spatial distribution of natural killer immune cells and five key genes within liver tumor tissues. "In Singapore, up to 70 per cent of liver cancer patients experience recurrence within five years," said Principal Investigator Joe Yeong from the IMCB, noting that this system empowers clinicians to intervene as early as possible. Researchers validated the system using tissue samples from 231 patients across five hospitals. It is now accessible via a free web portal for research purposes, with plans underway to integrate it into standard clinical workflows. Further validation studies are scheduled to begin later this year. UNI XINHUA AKT PRS
New Paper
3 days ago
- Health
- New Paper
Singapore AI system may help predict liver cancer recurrence
A scoring system powered by artificial intelligence (AI) that was developed by researchers here could help predict the recurrence of a common form of liver cancer. Developed by scientists from A*Star's Institute of Molecular and Cell Biology (IMCB) and Singapore General Hospital (SGH), the system can predict relapses of hepatocellular carcinoma (HCC). Affecting more than 20 out of every 100,000 people here annually, HCC is the fourth-most-common cancer among men in Singapore, as well as the third-most-common cause of cancer deaths among males here. The Tumour Immune Microenvironment Spatial (Times) score analyses the precise spatial distribution, or the exact location, of immune cells called natural killer (NK) cells and five specific genes within liver tumour tissues. NK cells are a type of white blood cell that destroys diseased cells, such as cancer cells, and a lower number of NK cells is an indicator of a higher risk of relapse. "Instead of just counting how many NK cells are present, we analyse exactly where they are positioned relative to the cancer cells," said Dr Joe Yeong, a principal investigator at both A*Star IMCB and SGH's anatomical pathology department. "By understanding how NK cells are distributed and how they interact with cancer cells - for example, whether they are close enough to attack the cancer effectively - we can predict the likelihood of cancer returning after surgery," said Dr Yeong, one of the study's authors. Identifying these spatial patterns allows Times to predict the risk of recurrence with about 82 per cent accuracy. Existing staging methods - frameworks that evaluate how advanced the cancer is, allowing doctors to recommend the most suitable treatments - vary in their accuracy. Dr Yeong - who is also director of immunopathology at the SingHealth Duke-NUS Pathology Academic Clinical Programme - noted that up to 70 per cent of liver cancer patients experience recurrence within five years. An accurate prediction method would allow doctors to more easily identify patients at greater risk of cancer recurrence, he said. "Times offers a significant advancement in predicting these outcomes, enabling clinicians to intervene at the earliest possible stage. This can significantly enhance patient care and improve survival outcomes." He noted that the precision medicine approach seeks to tailor treatments that meet patients' specific needs, based on factors such as genetics and lifestyle. Even though a large proportion of liver cancer patients experience relapses, it is not viable to offer all of them therapeutics as it would be very costly to them, Dr Yeong said. Getting an accurate prediction of their risks would help optimise the costs to patients, he added. AI was used to analyse vast amounts of data, with more than 100 trillion data points gathered from liver tumour samples, as well as create a scoring system tailored to Asian patients. It is also currently being used to refine the Times score for clinical use, Dr Yeong said. "By automating the analysis of patients' surgical tissue samples, AI ensures the process is efficient and consistent, paving the way for integration into routine clinical workflows, such as through a potential diagnostic test kit," he added. The study was the cover story for the April 15, 2025, issue of the peer-reviewed scientific journal Nature. Ms Denise Goh, the study's co-first author, said the Times scoring system "transforms routine tissue slides into powerful predictive tools". "By identifying patients at higher risk of relapse, we can proactively alter treatment strategies and monitoring, potentially saving more lives," said the senior research officer at A*Star IMCB. The researchers validated the accuracy of the Times system using samples from 231 patients across five hospitals in Singapore and China. The technology is now accessible through a free web portal for research use, with plans under way to integrate Times into routine clinical workflows. The team is planning further studies at SGH and the National Cancer Centre Singapore to validate the technology, scheduled to begin later in 2025. Discussions are ongoing with partners to develop Times into a clinically approved diagnostic test kit.
Straits Times
4 days ago
- Health
- Straits Times
AI system developed in Singapore could help predict liver cancer recurrence
Find out what's new on ST website and app. Dr Joe Yeong is a co-author of the study published in the peer-reviewed scientific journal Nature. SINGAPORE - A scoring system powered by artificial intelligence (AI) that was developed by researchers here could help predict the recurrence of a common form of liver cancer. Developed by scientists from A*Star's Institute of Molecular and Cell Biology (IMCB) and Singapore General Hospital (SGH), the system can predict relapses of hepatocellular carcinoma (HCC). Affecting more than 20 out of every 100,000 people here annually, HCC is the fourth-most-common cancer among men in Singapore, as well as the third-most-common cause of cancer deaths among males here. The Tumour Immune Microenvironment Spatial (Times) score analyses the precise spatial distribution, or the exact location, of immune cells called natural killer (NK) cells and five specific genes within liver tumour tissues. NK cells are a type of white blood cell that destroys diseased cells, such as cancer cells, and a lower number of NK cells is an indicator of a higher risk of relapse. 'Instead of just counting how many NK cells are present, we analyse exactly where they are positioned relative to the cancer cells,' said Dr Joe Yeong, a principal investigator at both A*Star IMCB and SGH's anatomical pathology department. 'By understanding how NK cells are distributed and how they interact with cancer cells – for example, whether they are close enough to attack the cancer effectively – we can predict the likelihood of cancer returning after surgery,' said Dr Yeong, one of the study's authors. Top stories Swipe. Select. Stay informed. Singapore Mindef, SAF units among those dealing with attack on S'pore's critical information infrastructure Asia How China's growing cyber-hacking capabilities have raised alarm around the world Asia At least 34 killed as tourist boat capsizes in Vietnam's Halong Bay Singapore 1 dead, 1 injured after dispute between neighbours at Yishun HDB block Singapore Vessels from Navy, SCDF and MPA to debut at Marina Bay in NDP maritime display Asia Autogate glitch at Malaysia's major checkpoints causes chaos for S'porean and foreign travellers Asia SIA, Scoot, Cathay Pacific cancel flights as typhoon nears Hong Kong Singapore A deadly cocktail: Easy access, lax attitudes driving Kpod scourge in S'pore Identifying these spatial patterns allows Times to predict the risk of recurrence with about 82 per cent accuracy. Existing staging methods – frameworks that evaluate how advanced the cancer is, allowing doctors to recommend the most suitable treatments – vary in their accuracy. Dr Yeong – who is also director of immunopathology at the SingHealth Duke-NUS Pathology Academic Clinical Programme – noted that up to 70 per cent of liver cancer patients experience recurrence within five years. An accurate prediction method would allow doctors to more easily identify patients at greater risk of cancer recurrence, he said. 'Times offers a significant advancement in predicting these outcomes, enabling clinicians to intervene at the earliest possible stage. This can significantly enhance patient care and improve survival outcomes.' He noted that the precision medicine approach seeks to tailor treatments that meet patients' specific needs, based on factors such as genetics and lifestyle. Even though a large proportion of liver cancer patients experience relapses, it is not viable to offer all of them therapeutics as it would be very costly to them, Dr Yeong said. Getting an accurate prediction of their risks would help optimise the costs to patients, he added. AI was used to analyse vast amounts of data, with more than 100 trillion data points gathered from liver tumour samples, as well as create a scoring system tailored to Asian patients. It is also currently being used to refine the Times score for clinical use, Dr Yeong said. 'By automating the analysis of patients' surgical tissue samples, AI ensures the process is efficient and consistent, paving the way for integration into routine clinical workflows, such as through a potential diagnostic test kit,' he added. The study was the cover story for the April 15, 2025, issue of the peer-reviewed scientific journal Nature. Ms Denise Goh, the study's co-first author, said the Times scoring system 'transforms routine tissue slides into powerful predictive tools'. 'By identifying patients at higher risk of relapse, we can proactively alter treatment strategies and monitoring, potentially saving more lives,' said the senior research officer at A*Star IMCB. The researchers validated the accuracy of the Times system using samples from 231 patients across five hospitals in Singapore and China. The technology is now accessible through a free web portal for research use, with plans under way to integrate Times into routine clinical workflows. The team is planning further studies at SGH and the National Cancer Centre Singapore to validate the technology, scheduled to begin later in 2025. Discussions are ongoing with partners to develop Times into a clinically approved diagnostic test kit.
