A5038559731- Advanced Chemical Sensor Technologies
- AI in cancer detection
- Diverse Approaches in Healthcare and Education Studies
- Technology and Data Analysis
- Diverse Topics in Contemporary Research
- Radiomics and Machine Learning in Medical Imaging
- Consumer Perception and Purchasing Behavior
- Analytical Chemistry and Sensors
- Cervical Cancer and HPV Research
- Global Trade and Competitiveness
- Biosensors and Analytical Detection
- Gas Sensing Nanomaterials and Sensors
- Cancer Immunotherapy and Biomarkers
- Gut microbiota and health
- Spectroscopy and Chemometric Analyses
- Global trade and economics
- Intracerebral and Subarachnoid Hemorrhage Research
- Customer Service Quality and Loyalty
- Firm Innovation and Growth
- International Business and FDI
- Endometrial and Cervical Cancer Treatments
- Fault Detection and Control Systems
- Technology Adoption and User Behaviour
- Advanced Battery Materials and Technologies
- Advanced Biosensing Techniques and Applications
Kyungpook National University
2021-2025
Korea University
2021-2022
Lowell Digisonde International (United States)
2020
University of Massachusetts Lowell
2011-2015
Hanseo University
2011-2013
Chonnam National University
2002-2003
East Carolina University
1995
The use of Convolutional Neural Networks (CNN) in natural image classification systems has produced very impressive results. Combined with the inherent nature medical images that make them ideal for deep-learning, further application such to holds much promise. However, usefulness and potential impact a system can be completely negated if it does not reach target accuracy. In this paper, we present study on determining optimum size training data set necessary achieve high accuracy low...
Screening is critical for prevention and early detection of cervical cancer but it time-consuming laborious. Supervised deep convolutional neural networks have been developed to automate pap smear screening the results are promising. However, interest in using only normal samples train has increased owing class imbalance problems high-labeling costs that both prevalent healthcare. In this study, we introduce a method learn explainable cell representations cytology images based on one-class...
Abstract Background Gut is a crucial organ for the host’s defense system due to its filtering action of intestinal membrane from hazardous foreign substances. One strategy strengthen gut epithelial barrier function upregulate beneficial microflora populations and their metabolites. Sophorolipid (SPL), which glycolipid bio-surfactant, could increase decrease pathogenic bacteria in gastrointestinal tract. Therefore, herein, we conducted an experiment with broiler chickens investigate...
Background and objectives: Telomerase reverse transcriptase (TERT) promoter mutation, found in a subset of patients with thyroid cancer, is strongly associated aggressive biologic behavior. Predicting TERT mutation thus necessary for the prognostic stratification cancer patients. Materials Methods: In this study, we evaluate status through deep learning approach using histologic images. Our analysis included 13 consecutive surgically resected cancers mutations (either C228T or C250T) 12...
Tumor microenvironment (TME) plays a pivotal role in immuno-oncology, which investigates the intricate interactions between tumors and human immune system. Specifically, tumor-infiltrating lymphocytes (TILs) are crucial biomarkers for evaluating prognosis of breast cancer patients have potential to refine immunotherapy precision accurately identify tumor cells specific types. In this study, we conducted tissue segmentation lymphocyte detection tasks predict TIL scores by employing...
Purpose This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by spectators each league (American and National League) division in MLB, authors will increase accuracy, discuss them provide implications marketing strategies academics sport. Design/methodology/approach used six years of daily MLB game data (2014–2019). All were collected as...
A wavelength calibration method for a charge-coupled device (CCD) array detector and seven-channel fiber-optic spectrograph is described. The was developed the extraction of wavelength-calibrated spectra in situ dissolution testing tablets. includes automatic recognition positions seven fiber channels mercury line pixel numbers. model with two trigonometric terms used least-squares fitting horizontal numbers to known wavelengths five lines from low-pressure discharge lamp. Four other models...
This paper aims to recognize explosive precursors using a nanowire sensor array and decision tree learning algorithm. The consisting of tin oxide sensors with four different additives, platinum (Pt), copper (Cu), indium (In), nickel (Ni) was designed, fabricated tested the vapors from precursors, acetone, nitrobenzene, nitrotoluene, octane, at eight concentration levels. A novel pattern recognition technique based on applied classify estimate their concentration. Classification regression...
Abstract Quartz Crystal Microbalance (QCM) based sensors have been used extensively to detect trace amounts of organic chemical vapors. These devices typically incorporate a polymer coating as an active layer that can bind the analytes interest. Analyte adsorption causes shift in resonant frequency device proportional amount adsorbed material. Currently some coatings these utilize hydrogen bonding adsorb analytes. Dipole-dipole type interactions also be utilized promote interaction with...