Singapore medical journal最新文献

{"title":"Development and validation of a deep learning system for detection of small bowel pathologies in capsule endoscopy: a pilot study in a Singapore institution.","authors":"Bochao Jiang, Michael Dorosan, Justin Wen Hao Leong, Marcus Eng Hock Ong, Sean Shao Wei Lam, Tiing Leong Ang","doi":"10.4103/singaporemedj.SMJ-2023-187","DOIUrl":"10.4103/singaporemedj.SMJ-2023-187","url":null,"abstract":"<p><strong>Introduction: </strong>Deep learning models can assess the quality of images and discriminate among abnormalities in small bowel capsule endoscopy (CE), reducing fatigue and the time needed for diagnosis. They serve as a decision support system, partially automating the diagnosis process by providing probability predictions for abnormalities.</p><p><strong>Methods: </strong>We demonstrated the use of deep learning models in CE image analysis, specifically by piloting a bowel preparation model (BPM) and an abnormality detection model (ADM) to determine frame-level view quality and the presence of abnormal findings, respectively. We used convolutional neural network-based models pretrained on large-scale open-domain data to extract spatial features of CE images that were then used in a dense feed-forward neural network classifier. We then combined the open-source Kvasir-Capsule dataset (n = 43) and locally collected CE data (n = 29).</p><p><strong>Results: </strong>Model performance was compared using averaged five-fold and two-fold cross-validation for BPMs and ADMs, respectively. The best BPM model based on a pre-trained ResNet50 architecture had an area under the receiver operating characteristic and precision-recall curves of 0.969±0.008 and 0.843±0.041, respectively. The best ADM model, also based on ResNet50, had top-1 and top-2 accuracies of 84.03±0.051 and 94.78±0.028, respectively. The models could process approximately 200-250 images per second and showed good discrimination on time-critical abnormalities such as bleeding.</p><p><strong>Conclusion: </strong>Our pilot models showed the potential to improve time to diagnosis in CE workflows. To our knowledge, our approach is unique to the Singapore context. The value of our work can be further evaluated in a pragmatic manner that is sensitive to existing clinician workflow and resource constraints.</p>","PeriodicalId":94289,"journal":{"name":"Singapore medical journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11060635/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140290115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opening a new chapter in health care: reporting on the inauguration of the International Conference on AI in Medicine.","authors":"Sanjay Haresh Chotirmall, Joseph J Y Sung","doi":"10.4103/singaporemedj.SMJ-2023-191","DOIUrl":"10.4103/singaporemedj.SMJ-2023-191","url":null,"abstract":"","PeriodicalId":94289,"journal":{"name":"Singapore medical journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11060634/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140290122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"COVID-19: down but not out.","authors":"Shawn Vasoo","doi":"10.4103/singaporemedj.SMJ-2024-041","DOIUrl":"10.4103/singaporemedj.SMJ-2024-041","url":null,"abstract":"","PeriodicalId":94289,"journal":{"name":"Singapore medical journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11073658/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140290124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes.","authors":"Kye Won Park, Maryam S Mirian, Martin J McKeown","doi":"10.4103/singaporemedj.SMJ-2023-189","DOIUrl":"10.4103/singaporemedj.SMJ-2023-189","url":null,"abstract":"<p><strong>Abstract: </strong>Due to global ageing, the burden of chronic movement and neurological disorders (Parkinson's disease and essential tremor) is rapidly increasing. Current diagnosis and monitoring of these disorders rely largely on face-to-face assessments utilising clinical rating scales, which are semi-subjective and time-consuming. To address these challenges, the utilisation of artificial intelligence (AI) has emerged. This review explores the advantages and challenges associated with using AI-driven video monitoring to care for elderly patients with movement disorders. The AI-based video monitoring systems offer improved efficiency and objectivity in remote patient monitoring, enabling real-time analysis of data, more uniform outcomes and augmented support for clinical trials. However, challenges, such as video quality, privacy compliance and noisy training labels, during development need to be addressed. Ultimately, the advancement of video monitoring for movement disorders is expected to evolve towards discreet, home-based evaluations during routine daily activities. This progression must incorporate data security, ethical considerations and adherence to regulatory standards.</p>","PeriodicalId":94289,"journal":{"name":"Singapore medical journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11060643/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140290112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"N-of-1 medicine.","authors":"Peter Wang, Qiao Ying Leong, Ni Yin Lau, Wei Ying Ng, Siong Peng Kwek, Lester Tan, Shang-Wei Song, Kui You, Li Ming Chong, Isaiah Zhuang, Yoong Hun Ong, Nigel Foo, Xavier Tadeo, Kirthika Senthil Kumar, Smrithi Vijayakumar, Yoann Sapanel, Marlena Natalia Raczkowska, Alexandria Remus, Agata Blasiak, Dean Ho","doi":"10.4103/singaporemedj.SMJ-2023-243","DOIUrl":"10.4103/singaporemedj.SMJ-2023-243","url":null,"abstract":"<p><strong>Abstract: </strong>The fields of precision and personalised medicine have led to promising advances in tailoring treatment to individual patients. Examples include genome/molecular alteration-guided drug selection, single-patient gene therapy design and synergy-based drug combination development, and these approaches can yield substantially diverse recommendations. Therefore, it is important to define each domain and delineate their commonalities and differences in an effort to develop novel clinical trial designs, streamline workflow development, rethink regulatory considerations, create value in healthcare and economics assessments, and other factors. These and other segments are essential to recognise the diversity within these domains to accelerate their respective workflows towards practice-changing healthcare. To emphasise these points, this article elaborates on the concept of digital health and digital medicine-enabled N-of-1 medicine, which individualises combination regimen and dosing using a patient's own data. We will conclude with recommendations for consideration when developing novel workflows based on emerging digital-based platforms.</p>","PeriodicalId":94289,"journal":{"name":"Singapore medical journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11060644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140290121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in medicine.","authors":"Mahesh Choolani","doi":"10.4103/singaporemedj.SMJ-2024-059","DOIUrl":"10.4103/singaporemedj.SMJ-2024-059","url":null,"abstract":"","PeriodicalId":94289,"journal":{"name":"Singapore medical journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11060637/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140290111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digitisation of emergency medicine: opportunities, examples and issues for consideration.","authors":"Kendall Ho","doi":"10.4103/singaporemedj.SMJ-2023-217","DOIUrl":"10.4103/singaporemedj.SMJ-2023-217","url":null,"abstract":"","PeriodicalId":94289,"journal":{"name":"Singapore medical journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11060638/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140290116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contrast-enhanced spectral mammography.","authors":"Christopher Yung Yuen Wong, Shu Yi Sonia Lee, Rameysh Danovani Mahmood","doi":"10.4103/singaporemedj.SMJ-2021-268","DOIUrl":"10.4103/singaporemedj.SMJ-2021-268","url":null,"abstract":"","PeriodicalId":94289,"journal":{"name":"Singapore medical journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11060636/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140290114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Value of robotic total knee arthroplasty in residency training: perceptions of orthopaedic surgery residents.","authors":"Gabriel Kai Yang Tan, Tong Leng Tan, Tamara Lee Ting Soh, Kelvin Guoping Tan","doi":"10.4103/singaporemedj.SMJ-2022-010","DOIUrl":"10.4103/singaporemedj.SMJ-2022-010","url":null,"abstract":"","PeriodicalId":94289,"journal":{"name":"Singapore medical journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139975342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Migraine and atrial fibrillation: a systematic review and meta-analysis.","authors":"Camelia Qi En Lim, Yao Neng Teo, Tony Yi-Wei Li, Yao Hao Teo, Nicholas Li-Xun Syn, Aloysius Sheng-Ting Leow, Jamie Sin-Ying Ho, Toon Wei Lim, Swee-Chong Seow, Mark Yan Yee Chan, Raymond Ching Chiew Wong, Ping Chai, Amanda Chee Yun Chan, Vijay Kumar Sharma, Benjamin Yong-Qiang Tan, Leonard Leong Litt Yeo, Jonathan Jia Yuan Ong, Ching-Hui Sia","doi":"10.4103/singaporemedj.SMJ-2022-114","DOIUrl":"https://doi.org/10.4103/singaporemedj.SMJ-2022-114","url":null,"abstract":"<p><strong>Background: </strong>Patients with migraines, particularly those with auras, may present with stroke. Atrial fibrillation is a known risk factor for stroke. With common pathophysiological factors between migraines and atrial fibrillation, we aimed to clarify the association between migraine and atrial fibrillation in this systematic review and meta-analysis.</p><p><strong>Methods: </strong>A literature search was conducted in EMBASE, PubMed, Scopus and Cochrane electronic bibliographic databases from inception to 5 September 2022 with the following inclusion criteria: (a) cohort or cross-sectional studies; (b) studies that included only patients aged ≥18 years; and (c) studies that examined the association between atrial fibrillation and migraines. Exclusion criteria were case-control studies and the studies that included patients with previous diagnosis of atrial fibrillation or nonmigrainous headache. The Newcastle-Ottawa Scale was used to assess the quality of studies.</p><p><strong>Results: </strong>Six studies were included, demonstrating a pooled prevalence of atrial fibrillation of 1.61% (95% confidence interval [CI] 0.51, 3.29) in migraine with aura and 1.32% (95% CI 0.17, 3.41) in migraine without aura. The overall prevalence of atrial fibrillation in migraine was 1.39% (95% CI 0.24, 3.46).</p><p><strong>Conclusion: </strong>In this systematic review and meta-analysis, the overall prevalence of atrial fibrillation in patients with migraine was low. Further studies are needed to clarify this relationship.</p>","PeriodicalId":94289,"journal":{"name":"Singapore medical journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139975340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}