摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据NewsRx编辑在新加坡的新闻报道，研究表明：“由于不断更新的临床实践指南和越来越多的可用药物类别，2型糖尿病(T2DM)的临床管理提出了一个重大挑战。证据表明，人工智能(AI)支持的临床决策支持系统(CDSSs)已被证明在帮助临床医生做出知情决策方面是有效的。”我们的新闻记者从新加坡国立大学医学院的研究中获得了一句话，“尽管人工智能驱动的CDSS有优点，但在T2DM管理中人工智能支持的CDSS的早期实施和选择方面存在重大的研究差距。本研究旨在探索临床医生对人工智能支持的处方咨询(APA)工具的使用和影响的观点。”使用多机构糖尿病登记处开发，并在专科内分泌诊所实施，我们使用半结构化访谈指南对某三级医院的内分泌科医生进行了焦点小组讨论，焦点小组讨论被录音和逐字记录，并对数据进行了主题分析，共13名临床医生参加了4次焦点小组讨论。我们的发现表明，APA工具提供了几个有用的功能来帮助临床医生有效地进行治疗。管理T2DM。具体地说，临床医生认为人工智能产生的药物改变是一个很好的知识资源，可以支持临床医生在治疗过程中做出药物修改的决策，特别是对于合并症患者。并发症风险预测被认为通过促进早期医患沟通和启动及时的临床反应，对患者护理产生积极影响。然而，风险评分的可解释性，对过度依赖和自动偏倚的担忧，"围绕责任和责任的问题阻碍了APA工具在临床实践中的应用."
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting out of Singapore, Sing apore, by NewsRx editors, research stated, "The clinical management of type 2 di abetes mellitus (T2DM) presents a significant challenge due to the constantly ev olving clinical practice guidelines and growing array of drug classes available. Evidence suggests that artificial intelligence (AI)-enabled clinical decision s upport systems (CDSSs) have proven to be effective in assisting clinicians with informed decision-making." Our news journalists obtained a quote from the research from the Duke-National U niversity of Singapore Medical School, "Despite the merits of AI-driven CDSSs, a significant research gap exists concerning the early-stage implementation and a doption of AI-enabled CDSSs in T2DM management. This study aimed to explore the perspectives of clinicians on the use and impact of the AI-enabled Prescription Advisory (APA) tool, developed using a multi-institution diabetes registry and i mplemented in specialist endocrinology clinics, and the challenges to its adopti on and application. We conducted focus group discussions using a semistructured interview guide with purposively selected endocrinologists from a tertiary hospi tal. The focus group discussions were audio-recorded and transcribed verbatim. D ata were thematically analyzed. A total of 13 clinicians participated in 4 focus group discussions. Our findings suggest that the APA tool offered several usefu l features to assist clinicians in effectively managing T2DM. Specifically, clin icians viewed the AI-generated medication alterations as a good knowledge resour ce in supporting the clinician's decision-making on drug modifications at the po int of care, particularly for patients with comorbidities. The complication risk prediction was seen as positively impacting patient care by facilitating early doctorpatient communication and initiating prompt clinical responses. However, the interpretability of the risk scores, concerns about overreliance and automat ion bias, and issues surrounding accountability and liability hindered the adopt ion of the APA tool in clinical practice."
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