Integration of Electrochemical Sensing and Machine Learning to Detect Tuberculosis via Methyl Nicotinate in Patient Breath
Jeppson, M. A.; Rasmussen, Z.; Castro, R.; Nalugwa, T.; Kisakye, E.; Mangeni, W.; Andama, A.; Jaganath, D.; Cattamanchi, A.; Mohanty, S. K.
Show abstract
Tuberculosis (TB) remains a significant global health issue; making early, accurate, and inexpensive point-of-care detection critical for effective treatment. This paper presents a clinical demonstration of an electrochemical sensor that detects methyl-nicotinate (MN), a volatile organic biomarker associated with active pulmonary tuberculosis. The sensor was initially tested on a patient cohort comprised of 57 adults in Kampala, Uganda, of whom 42 were microbiologically confirmed TB-positive and 15 TB-negative. The sensor employed a copper(II) liquid metal salt solution with a square wave voltammetry method tailored for MN detection using commercially available screen-printed electrodes. An exploratory machine learning analysis was performed using XGBOOST. Utilizing this approach, the sensor was 78% accurate with 71% sensitivity and 100% specificity. These initial results suggest the sensing methodology is effective in identifying TB from complex breath samples, providing a promising tool for non-invasive and rapid TB detection in clinical settings.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Generation of false positive SARS-CoV-2 antigen results with testing conditions outside manufacturer recommendations: A scientific approach to pandemic misinformation 92%
- Co-occurrence of Direct and Indirect Extracellular Electron Transfer Mechanisms during Electroactive Respiration in a Dissimilatory Sulfate Reducing Bacterium 92%
- Machine-learning based detection of adventitious microbes in T-cell therapy cultures using long read sequencing 91%
Similar papers in this journal
- Low-cost, local production of a safe and effective disinfectant for resource-constrained communities 94%
- Respiratory virus infection dynamics and genomic surveillance to detect seasonal influenza subtypes in wastewater: a longitudinal study in Bengaluru, India 90%
- Prevalence and determinants of evidence of silicosis and impaired lung function, among small scale tanzanite miners and the peri-mining community in northern Tanzania 89%
Similar papers in this journal
- Analytical performance of 17 commercially available point-of-care tests for CRP to support patient management at lower levels of the health system 93%
- Direct Detection and Identification of Viruses in Saliva Using a SpecID™ Ionization Modified Mass Spectrometer 92%
- You Only Look Once (YOLO) Based Machine Learning Algorithm for Real-Time Detection of Loop-Mediated Isothermal Amplification (LAMP) Diagnostics 92%
Similar papers in this journal
- Electrical Readout Strategies of GFET Biosensors for Real-World Requirements 95%
- Electrochemical detection of myeloperoxidase (MPO) in blood plasma with surface-modified electroless nickel immersion gold (ENIG) printed circuit board (PCB) electrodes 94%
- Development of a Microelectrode Array System for Simultaneous Measurement of Field Potential and Glutamate Release in Brain Slices 93%
Similar papers in this journal
- A low power flexible dielectric barrier discharge disinfects surfaces and improves the action of hydrogen peroxide 93%
- Development and Clinical Validation of Swaasa AI Platform for screening and prioritization of Pulmonary TB 92%
- Optical tuning of polymer functionalized zinc oxide quantum dots as a selective probe for specific detection of antibiotics 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.