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编辑在德国波鸿的新闻报道，研究表明：“单阶段乳房固定术由于其复杂性和相对较高的GH并发症发生率，是一种备受争议的干预措施。本研究旨在使用基于人工智能的新方法重新评估这些并发症的危险因素，并揭示其可能的局限性。”我们的新闻记者从BG大学医院获得了一段研究的引文：“回顾性收集2014-2023年期间由单一外科医生在一个机构进行一次性隆胸MAS固定的完整数据集，随后用CART、RF和XG Boost算法进行处理和分析。共纳入342例患者，其中43例(12.57%)报告了手术相关并发症。其中以头肌挛缩症(n=19)最常见,BMI是并发症发生的最重要变量(CART中的FIS=0.44),2.9%的患者表示希望在病程中更换种植体,吸烟与种植体更换愿望之间有统计学意义(P<0.001),提示人工智能应用于临床研究的重要性。由于风险变量可以根据以前认为较少甚至不相关的因素重新分类，因此我们使用ML方法遇到了D限制。需要进一步研究吸烟、BMI和当前种植体尺寸与种植体改变设计的关系，并且没有任何并发症。此外，我们还需要进一步研究，以了解吸烟、BMI和当前种植体尺寸与种植体改变设计的关系。我们可以证明，这种手术可以安全地进行，而不存在发生严重并发症的高风险。本杂志要求作者为每一篇文章分配一定程度的证据。
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 Bochum, Germany , by NewsRx editors, research stated, "Single-stage mastopexy augmentation is a much-debated intervention due to its complexity and the associated relatively hi gh complication rates. This study aimed to reevaluate the risk factors for these complications using a novel approach based on artificial intelligence and to de monstrate its possible limitations." Our news journalists obtained a quote from the research from BG-University Hospi tal, "Complete datasets of patients who underwent single-staged augmentation mas topexy during 2014-2023 at one institution by a single surgeon were collected re trospectively. These were subsequently processed and analyzed by CART, RF and XG Boost algorithms. A total of 342 patients were included in the study, of which 4 3 (12.57%) reported surgery-associated complications, whereby capsu lar contracture (n = 19) was the most common. BMI represented the most important variable for the development of complications (FIS = 0.44 in CART). 2.9% of the patients expressed the desire for implant change in the course, with abse nce of any complications. A statistically significant correlation between smokin g and the desire for implant change (p <0.001) was reveale d. The importance of implementing artificial intelligence into clinical research could be underpinned by this study, as risk variables can be reclassified based on factors previously considered less or even irrelevant. Thereby we encountere d limitations using ML approaches. Further studies will be needed to investigate the association between smoking, BMI and the current implant size with the desi re for implant change without any complications. Moreover, we could show that th e procedure can be performed safely without high risk of developing major compli cations. This journal requires that authors assign a level of evidence to each a rticle."
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