0000000001079170

AUTHOR

Juha M. Kortelainen

showing 3 related works from this author

Repeatability Study on a Classifier for Gastric Cancer Detection from Breath Sensor Data

2019

The SNIFFPHONE device is a portable multichannel gas sensor, aiming to detect gastric cancer (GC) from breath samples. It employs gold nanoparticle (GNP) sensors reacting to volatile organic compounds (VOCs) in the exhaled breath, a non-invasive technique to support early diagnosis. This study evaluates the repeatability of the SNIFFPHONE classification result for measurements conducted on healthy subjects over a short period of time of less than 10 minutes. Due to the portable nature of the device, repeatability is studied with respect to varying measurement location. We find the classification results repeatable with a statistically significant 81 % Pearson correlation coefficient, even t…

business.industryBreath sensorHealthy subjects02 engineering and technologyCancer detectionRepeatability021001 nanoscience & nanotechnologyCancer detectionPearson product-moment correlation coefficient03 medical and health sciencessymbols.namesake0302 clinical medicineSDG 3 - Good Health and Well-beingVolatile organic compunds030220 oncology & carcinogenesisClassification resultsymbolsMedicine/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingDecision support for health0210 nano-technologybusinessGastric cancerClassifier (UML)Biomedical engineering
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Overview on SNIFFPHONE:A portable device for disease diagnosis

2019

We present SNIFFPHONE, a handy and easy-To-use device that allows the non-invasive detection of gastric diseases. It analyzes the user's exhaled breath using specifically developed gas sensors. The device is coupled to a smartphone, which governs the breath analysis process, sends the data measurements to an external data analysis server, and finally gives feedback to the user. In this work, we describe the SNIFFPHONE device and the general platform under development.

SNIFFPHONEComputer sciencegastrointestinal cancerProcess (computing)DiseaseGastric Diseasesgas sensorExternal dataBreath gas analysisSDG 3 - Good Health and Well-beingHuman–computer interaction/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingbreath analysis
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Sensing gastric cancer via point‐of‐care sensor breath analyzer

2021

Background Detection of disease by means of volatile organic compounds from breath samples using sensors is an attractive approach to fast, noninvasive and inexpensive diagnostics. However, these techniques are still limited to applications within the laboratory settings. Here, we report on the development and use of a fast, portable, and IoT-connected point-of-care device (so-called, SniffPhone) to detect and classify gastric cancer to potentially provide new qualitative solutions for cancer screening. Methods A validation study of patients with gastric cancer, patients with high-risk precancerous gastric lesions, and controls was conducted with 2 SniffPhone devices. Linear discriminant an…

AdultMaleCancer ResearchValidation studymedicine.medical_specialtyvolatile organic compoundPoint-of-Care SystemsBiosensing TechniquesSensitivity and Specificity03 medical and health sciences0302 clinical medicineSDG 3 - Good Health and Well-beingbreath analyzerStomach NeoplasmsCancer screeningmedicineHumansNanotechnology030212 general & internal medicinePoint of careAgedAged 80 and overbusiness.industrygastric cancerscreeningCancerpersonalizedDiscriminant AnalysisGastric lesionsMiddle Agedmedicine.diseaseLinear discriminant analysisprecancerous lesion3. Good healthBreath analyzerOncologyBreath Tests030220 oncology & carcinogenesisArea Under CurveCase-Control Studies/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingFemaleRadiologyInternet of ThingsbusinessPrecancerous ConditionsCancer
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