Clarence Mrcp Kwan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Clarence Mrcp Kwan has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Baldwin Po Man Yeung
Department of General Surgery, Sengkang General Hospital, Singapore
1 shared publication - Frederick Hong Xiang Koh
Correspondence to: Frederick H. Koh, MBBS, MMed (Surg), FRCS, PhD Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Rd, Singapore 308232
1 shared publication - Fung Joon Foo
Colorectal Service, Department of General Surgery, Sengkang General Hospital, Singapore
1 shared publication - Gabrielle E. Koh
Department of General Surgery, Sengkang General Hospital, Singapore
1 shared publication - James Weiquan Li
Department of Gastroenterology, Sengkang General Hospital, Singapore
1 shared publication Jayden W. Mbbs Yap
Yong Loo Lin School of Medicine, National University of Singapore, Singapore
1 shared publication
Latest Publications
- Open Access
- 20 April 2026
- Published by Wolters Kluwer Health in International Journal of Surgery
- Vol. 112 (6) , 12742-12748
Computer-Assisted Detection (CADe) of colonic polyps during colonoscopy reduces cancer-related healthcare costs – a single Singaporean institution cost effectiveness analysis
Background and aims: Colonoscopy remains as an invaluable diagnostic and therapeutic tool used for the screening and evaluation of colonic pathologies. Periodic endoscopic screening allowing for early detection and removal of pre-malignant lesions, resulting in significant overall decreased incidence and mortality from colorectal cancer. Despite its added costs, artificial intelligence (AI) has been increasingly utilized in the field of endoscopy, boasting benefits of improving adenoma detection rates while reducing endoscopists’ mental fatigue intra-procedurally. As such, further evaluation of the financial impact of such AI-usage in screening colonoscopies was performed to assess if routine use of AI-guidance in screening colonoscopies was justifiable. Methods: This study conducted a cost effectiveness analysis of the GI Genius™ CADx Intelligent Endoscopy Module (US-DG-2000309, 2021 Medtronic) system in our local Singaporean tertiary public healthcare institution. A decision tree model was used to calculate Incremental Cost Effectiveness Ratio (ICER), comparing cancer-related costs for patients who underwent conventional colonoscopy versus colonoscopy with AI guidance. Results: With a calculated ICER value of 0.72, our study suggests that AI-assisted colonoscopy was indeed cost effective. Quality-Adjusted Life Years (QALY) values derived for each subgroup of patients further demonstrated overall improved quality of life reported by patients who underwent AI-assisted colonoscopy, as compared to conventional colonoscopy. Conclusion: Our study supports the incorporation of AI guidance into routine colonoscopic evaluation in view of increased cost effectiveness and improved overall quality of life achieved. However, further studies and analysis must be undertaken before reliably determining the cost-effectiveness of AI on regional or international scales.
- 20 April 2026
- Published by Wolters Kluwer Health in International Journal of Surgery
- Vol. 112 (6) , 12742-12748
Open AccessComputer-Assisted Detection (CADe) of colonic polyps during colonoscopy reduces cancer-related healthcare costs – a single Singaporean institution cost effectiveness analysis
Background and aims: Colonoscopy remains as an invaluable diagnostic and therapeutic tool used for the screening and evaluation of colonic pathologies. Periodic endoscopic screening allowing for early detection and removal of pre-malignant lesions, resulting in significant overall decreased incidence and mortality from colorectal cancer. Despite its added costs, artificial intelligence (AI) has been increasingly utilized in the field of endoscopy, boasting benefits of improving adenoma detection rates while reducing endoscopists’ mental fatigue intra-procedurally. As such, further evaluation of the financial impact of such AI-usage in screening colonoscopies was performed to assess if routine use of AI-guidance in screening colonoscopies was justifiable. Methods: This study conducted a cost effectiveness analysis of the GI Genius™ CADx Intelligent Endoscopy Module (US-DG-2000309, 2021 Medtronic) system in our local Singaporean tertiary public healthcare institution. A decision tree model was used to calculate Incremental Cost Effectiveness Ratio (ICER), comparing cancer-related costs for patients who underwent conventional colonoscopy versus colonoscopy with AI guidance. Results: With a calculated ICER value of 0.72, our study suggests that AI-assisted colonoscopy was indeed cost effective. Quality-Adjusted Life Years (QALY) values derived for each subgroup of patients further demonstrated overall improved quality of life reported by patients who underwent AI-assisted colonoscopy, as compared to conventional colonoscopy. Conclusion: Our study supports the incorporation of AI guidance into routine colonoscopic evaluation in view of increased cost effectiveness and improved overall quality of life achieved. However, further studies and analysis must be undertaken before reliably determining the cost-effectiveness of AI on regional or international scales.