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Bronchoalveolar Lavage Fluid

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[Evaluation of the lateral flow Aspergillus assay for the diagnosis of invasive aspergillosis, experience in a university hospital].

Revista chilena de infectologia : organo oficial de la Sociedad Chilena de Infectologia
BACKGROUND: The incidence of invasive aspergillosis is increasing. Its diagnosis is based on clinical and microbiological criteria which include the determination of serological markers such as galactomannan. Recently, the Aspergillus lateral flow de...

Automated interpretation and analysis of bronchoalveolar lavage fluid.

International journal of medical informatics
BACKGROUND: The cytological analysis of bronchoalveolar lavage fluid (BALF) plays an essential role in the differential diagnosis of respiratory diseases. In recent years, deep learning has demonstrated excellent performance in image processing and o...

Cytologic scoring of equine exercise-induced pulmonary hemorrhage: Performance of human experts and a deep learning-based algorithm.

Veterinary pathology
Exercise-induced pulmonary hemorrhage (EIPH) is a relevant respiratory disease in sport horses, which can be diagnosed by examination of bronchoalveolar lavage fluid (BALF) cells using the total hemosiderin score (THS). The aim of this study was to e...

Deep Learning Neural Network-Guided Detection of Asbestos Bodies in Bronchoalveolar Lavage Samples.

Acta cytologica
INTRODUCTION: Asbestos is a global occupational health hazard, and exposure to it by inhalation predisposes to interstitial as well as malignant pulmonary morbidity. Over time, asbestos fibers embedded in lung tissue can become coated with iron-rich ...

Leukocyte differentiation in bronchoalveolar lavage fluids using higher harmonic generation microscopy and deep learning.

PloS one
BACKGROUND: In diseases such as interstitial lung diseases (ILDs), patient diagnosis relies on diagnostic analysis of bronchoalveolar lavage fluid (BALF) and biopsies. Immunological BALF analysis includes differentiation of leukocytes by standard cyt...

Deciphering the microbial landscape of lower respiratory tract infections: insights from metagenomics and machine learning.

Frontiers in cellular and infection microbiology
BACKGROUND: Lower respiratory tract infections represent prevalent ailments. Nonetheless, current comprehension of the microbial ecosystems within the lower respiratory tract remains incomplete and necessitates further comprehensive assessment. Lever...

Integrating respiratory microbiome and host immune response through machine learning for respiratory tract infection diagnosis.

NPJ biofilms and microbiomes
At present, the diagnosis of lower respiratory tract infections (LRTIs) is difficult, and there is an urgent need for better diagnostic methods. This study enrolled 136 patients from 2020 to 2021 and collected bronchoalveolar lavage fluid (BALF) spec...

Automated recognition and segmentation of lung cancer cytological images based on deep learning.

PloS one
Compared with histological examination of lung cancer, cytology is less invasive and provides better preservation of complete morphology and detail. However, traditional cytological diagnosis requires an experienced pathologist to evaluate all sectio...