机器学习用于识别临床相关的Candida酵母菌种类
Shamanth A Shankarnarayan1, Daniel A Charlebois1,2
1Department of Physics, University of Alberta, Edmonton, Alberta, T6G-2E1, Canada.
Medical mycology
|December 22, 2023
概括
机器学习可以从显微镜图像中准确识别Candida物种. 发明V3模型表现最好,改善了关键真菌病原体的识别率.
科学领域:
- 医学真菌学 医学真菌学
- 计算生物学 计算生物学
- 医疗信息学 医疗信息学
背景情况:
- 菌感染的发病率上升,特别是Candida物种.
- 在快速和准确的识别多药耐药性Candida auris.挑战.
- 机器学习在医疗保健和医学成像中的应用越来越多.
研究的目的:
- 评估六个卷积神经网络 (CNN) 的有效性,以识别四种临床意义上的Candida物种.
- 用显微镜图像来比较不同CNN架构的性能.
- 为了确定最佳的机器学习方法来识别Candida物种.
主要方法:
- 获取Candida物种的湿装显微镜图像.
- 将图像分为单细胞,芽细胞和细胞组类别.
- 应用六种机器学习算法 (定制CNN,VGG16,ResNet50,InceptionV3,EfficientNetB0,EfficientNetB7) 来进行物种预测.
主要成果:
- InceptionV3在从显微镜图像中预测Candida物种方面表现出卓越的表现.
- 所有模型在原始,未经处理的图像上表现不佳,但在单细胞和芽细胞图像上有所改善.
- InceptionV3在识别C. albicans,C. auris,C. glabrata和C. haemulonii的芽和单细胞方面取得了很高的准确率.
结论:
- 湿装幻灯片的显微镜图像可以有效地利用机器学习来快速准确地识别Candida酵母物种.
- InceptionV3模型显示了在真菌诊断中临床应用的巨大潜力.
- 进一步开发机器学习模型可以提高识别具有挑战性的真菌病原体的速度和准确性.
相关概念视频
Methods of Classification and Identification
Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
Rapid Identification of Pathogens
MALDI-TOF MS has transformed clinical microbiology by offering a rapid and reliable method for pathogen identification. The traditional approach to microbial identification typically involves time-consuming culture techniques and biochemical tests, which can delay the initiation of appropriate antimicrobial therapy. MALDI-TOF MS avoids these delays by using characteristic ribosomal protein mass patterns of microbial cells, enabling accurate species-level identification within minutes.Principle...
Automated Microbial Diagnostics
Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...
Candidiasis
Candidiasis is a fungal infection caused by opportunistic species of Candida. It can affect various anatomical sites, including the skin, oral cavity, nails, and genitourinary tract. Among its forms, vaginal candidiasis is the most common type of mucosal infection. It typically results from the overgrowth of Candida albicans in the vaginal mucosa. Under normal conditions, C. albicans exists as a commensal organism within the vaginal microbiota, regulated by the dominance of lactobacilli, which...


