The development of deep learning systems in artificial intelligence (AI) has enabled advances in endoscopy, and AI-aided colonoscopy has recently been ushered into clinical practice as a clinical decision-support tool. This has enabled real-time AI-aided detection of polyps with a higher sensitivity than the average endoscopist, and evidence to support its use has been promising thus far. This review article provides a summary of currently published data relating to AI-aided colonoscopy, discusses current clinical applications, and introduces ongoing research directions. We also explore endoscopists’ perceptions and attitudes toward the use of this technology, and discuss factors influencing its uptake in clinical practice.

INTRODUCTIONKnowledge of stroke symptoms is associated with seeking medical attention early, and knowledge of risk factors is an essential factor in stroke prevention. In this study, we evaluated the level of stroke literacy in Singapore.

MATERIALS AND METHODSA cross-sectional study of Singapore citizens and permanent residents aged 21 years and above was conducted in a public housing estate. Participants were randomly sampled using multi-stage stratified sampling. Assessment of awareness of stroke symptoms and risk factors was performed using open-ended questions. In total, 687 respondents were recruited, with a response rate of 69.7%.

RESULTSOverall, 52.4% of respondents identified the brain as the source of pathology, and 47.6% could cite at least 1 of the 3 FAST symptoms (facial droop, arm weakness and speech difficulty), while 40% could name 2 or more of 7 established risk factors for stroke (high blood pressure, high cholesterol, cigarette smoking, diabetes mellitus, older age, previous heart attacks and stroke). Respondents at higher risk of stroke (older individuals and those with stroke risk factors) did not have greater awareness of stroke symptoms and risk factors. The majority of respondents reported they would seek immediate medical care if they experienced stroke symptoms. Only 59.4% knew the emergency ambulance service telephone number.

CONCLUSIONIn a sample of Singaporean adults residing in a public housing estate, we found evidence of poor stroke literacy, highlighting the need for comprehensive population-based education efforts. There is a role for opportunistic education among those at higher risk of stroke.

Adult ; Aged ; Cross-Sectional Studies ; Female ; Health Literacy ; Humans ; Male ; Middle Aged ; Public Housing ; Risk Factors ; Singapore ; Socioeconomic Factors ; Stroke ; Surveys and Questionnaires ; Young Adult

Asian People ; Humans ; Prevalence ; Stereotyping