Comparing electronic nose (e-nose) performance is a challenging task because of a lack of standardised method. This paper proposes a method for defining and quantifying an indicator of the effectiveness of multi-sensor systems in detecting cancers by artificial breath analysis. To build this method, an evaluation of the performances of an array of metal oxide sensors built for use as a lung cancer screening tool was conducted. Breath from 20 healthy volunteers has been sampled in fluorinated ethylene propylene sampling bags. These healthy samples were analysed with and without the addition of nine volatile organic compound (VOC) cancer biomarkers, chosen from literature. The concentration of the VOC added was done in increasing amounts. The more VOC were added, the better the discrimination between 'healthy' samples (breath without additives) and 'cancer' samples (breath with additives) was. By determining at which level of concentration the e-nose fails to reliably discriminate between the two groups, we estimate its ability to well predict the presence of the disease or not in a realistic situation. In this work, a home-made e-nose is put to the test. The results underline that the biomarkers need to be about 5.3 times higher in concentration than in real breath for the home-made nose to tell the difference between groups with a sufficient confidence.
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http://dx.doi.org/10.1088/1752-7163/ad1d64 | DOI Listing |
J Coll Physicians Surg Pak
January 2025
Department of Emergency Medicine, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
The Valsalva manoeuvre is widely recognised for its effectiveness in reverting supra-ventricular tachycardia (SVT) in patients with good coordination. However, this is not applicable in sedated ventilated patients and there is a dearth of literature regarding the application of Valsalva in unconscious patients on mechanical ventilation. The authors, for the first time, present a novel non-pharmacological method to treat SVT in critically ill patients on mechanical ventilation, employing the high positive end-expiratory pressure (PEEP) technique.
View Article and Find Full Text PDFJ Coll Physicians Surg Pak
January 2025
Department of Pathology, National Institute of Cardiovascular Diseases, Karachi, Pakistan.
Objective: To determine the frequency of multidrug-resistant (MDR) bacterial isolates in respiratory specimens obtained from ventilated patients admitted to critical care units at the National Institute of Cardiovascular Diseases (NICVD), along with COVID-19-positive cases.
Study Design: An observational study. Place and Duration of the Study: National Institute of Cardiovascular Diseases, between November 2021 and March 2022.
BMC Med Inform Decis Mak
January 2025
Department of Clinical Pharmacy and Translational Science, The University of Tennessee Health Science Center, Memphis, TN, USA.
Background: The COVID-19 pandemic has highlighted the crucial role of artificial intelligence (AI) in predicting mortality and guiding healthcare decisions. However, AI models may perpetuate or exacerbate existing health disparities due to demographic biases, particularly affecting racial and ethnic minorities. The objective of this study is to investigate the demographic biases in AI models predicting COVID-19 mortality and to assess the effectiveness of transfer learning in improving model fairness across diverse demographic groups.
View Article and Find Full Text PDFJ Allergy Clin Immunol Pract
January 2025
Breathing Institute, Children's Hospital Colorado, Department of Pediatrics, Pediatric Pulmonary and Sleep Medicine Section, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO. Electronic address:
Digital health is an umbrella term for components of healthcare utilizing computer platforms, software, connectivity and sensors to augment the recording, documentation and communication of clinical information. The functions of digital health may be viewed in three domains: 1) the repository for patient information, 2) monitoring devices and 3) communication tools. Monitoring devices have provided robust information as diagnostic and prognostic tools in office and hospital settings.
View Article and Find Full Text PDFPLoS One
January 2025
National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Introduction: Haemodynamic atrioventricular delay (AVD) optimisation has primarily focussed on signals that are not easy to acquire from a pacing system itself, such as invasive left ventricular catheterisation or arterial blood pressure (ABP). In this study, standard clinical central venous pressure (CVP) signals are tested as a potential alternative.
Methods: Sixteen patients with a temporary pacemaker after cardiac surgery were studied.
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