# Advancements and Prospects of Electronic Nose in Various Applications: A Comprehensive Review
## 3 Application Areas
### Disease Diagnosis
#### 3.3.1 Human Clinical Pathology
Specifically, a study reported the successful differentiation of uninfected and infected urine samples containing _Escherichia coli_, _Proteus mirabilis_, and _Staphylococcus_ species using an e-nose [161]. This underscores the potential of e-noses in medical diagnostics and advancing our understanding of microbial intricacies. Breath analysis using e-nose technology faces numerous challenges in detecting volatile organic compounds (VOCs) associated with respiratory diseases like chronic obstructive pulmonary disease (COPD) amidst the complex mixture of compounds present in breath. Breath composition is diverse, encompassing VOCs originating from metabolic processes, environmental exposures, and physiological factors, posing a significant challenge in isolating COPD-linked VOCs accurately. One major hurdle is the presence of background noise in breath samples, consisting of various VOCs unrelated to the targeted respiratory condition. These background compounds can obscure the signals of interest, complicating the identification of VOCs indicative of COPD. Overcoming this challenge necessitates advanced sensor arrays capable of detecting a broad spectrum of VOCs while maintaining selectivity for disease-specific compounds [163; 164; 165]. Additionally, breath samples from COPD patients may exhibit variability in VOC concentrations due to factors like disease severity, comorbidities, and individual physiological differences. This variability adds complexity to breath analysis, requiring robust statistical methods and machine learning algorithms to distinguish between COPD-related VOC patterns and non-specific fluctuations. Moreover, confounding factors such as environmental contaminants, dietary influences, and medications further complicate breath sample analysis. These factors introduce additional variability and ambiguity into VOC profiles, demanding careful consideration and data preprocessing techniques to mitigate their impact on analysis results. Despite these challenges, the Cyranose 320 e-nose, developed by Cyranose Sciences and later known as Smiths Detection-Pasadena Inc. (Stateline, NV, USA), has demonstrated notable success in deciphering breath patterns associated with COPD [163; 164; 165]. Equipped with the patented NoseChip(tm) containing an array of 32 sensors utilizing single-wall carbon nanotubes, metallic nanoparticles, and conductive composites, the Cyranose 320 (CyranoSciences Inc., Pasadena, CA, USA) offers a modular design for the exchange of thin film nanosensors, enhancing its versatility [166]. Through the integration of its sensor array and sophisticated data analysis algorithms, the Cyanrose 320 has proven proficient in distinguishing between breath profiles of COPD patients and those of healthy individuals. Additionally, it has played a pivotal role in discriminating volatile organic compounds (VOCs) among patients with COVID-19 and post-COVID syndrome (see Figure 8) [167]. Notably, the device exhibits an impressive ability to differentiate between the breath fingerprints of COPD patients and non-infected subjects, achieving a success rate of 75% [163]. Furthermore, studies have showcased the Cyanrose 320's proficiency in delineating breath profiles between lung cancer patients and individuals with COPD [167]. Its contribution extends beyond COPD, as it has been instrumental in identifying distinct VOC signatures associated with various respiratory conditions, underscoring its potential as a valuable diagnostic tool in respiratory medicine. To further contextualize the broad landscape of e-nose applications in medical diagnostics, we present Table 5, showcasing a comprehensive range of biomedical applications developed using commercial and experimental electronic noses.