Article
Computer Science, Information Systems
Zichen Zhang, Shifei Ding, Yuting Sun
Summary: This paper introduces a new method called multiple birth support vector regression (MBSVR), which constructs the regressor from multiple hyperplanes obtained by solving small quadratic programming problems, aiming for faster computation and better fitting precision.
INFORMATION SCIENCES
(2021)
Article
Chemistry, Analytical
Nadezhda A. Taranova, Nadezhda A. Byzova, Svetlana M. Pridvorova, Anatoly Zherdev, Boris B. Dzantiev
Summary: Through a comparative study of different preparation parameters, it was found that gold nanoflowers prepared under specific conditions can improve the detection limits in lateral flow immunoassays, with more significant effects under instrumental detection. This improvement is mainly due to the low nonspecific binding of gold nanoflowers to the labels.
Article
Computer Science, Information Systems
Guoquan Li, Linxi Yang, Zhiyou Wu, Changzhi Wu
Summary: Proximal support vector machine (PSVM) is a variant of support vector machine (SVM) which aims to generate a pair of non-parallel hyperplanes for classification. Introducing l(0)-norm regularization in PSVM enables simultaneous selection of important features and removal of redundant features for classification. The proposed method utilizes a continuous nonconvex function and difference of convex functions algorithms (DCA) to solve the optimization problem efficiently.
INFORMATION SCIENCES
(2021)
Review
Chemistry, Medicinal
Isami Tsuboi, Katsuhiro Iinuma
Summary: Membrane-based rapid test reagents, including immunochromatography, are widely used in clinical practice. Recently, high-sensitive reagents based on immunochromatography, such as silver amplification method and time resolved fluorescence method for influenza testing, have been developed. In addition, genetic testing, which automates all steps from extraction to detection, is becoming increasingly popular, with examples like the Smart Gene Myco system for mycoplasma and COVID-19 testing.
CHEMICAL & PHARMACEUTICAL BULLETIN
(2021)
Article
Chemistry, Multidisciplinary
Vera A. Bragina, Elena Khomyakova, Alexey V. Orlov, Sergey L. Znoyko, Elizaveta N. Mochalova, Liliia Paniushkina, Victoria O. Shender, Thalia Erbes, Evgeniy G. Evtushenko, Dmitry V. Bagrov, Victoria N. Lavrenova, Irina Nazarenko, Petr I. Nikitin
Summary: This research developed a highly sensitive and easy-to-use immunochromatographic tool for the quantification of extracellular vesicles (EVs). The tool demonstrates advantages in detection limit, specificity, and cost-effectiveness, and can be used for liquid biopsy in daily clinical routines and extended to other relevant biomarkers.
Article
Environmental Sciences
Guangxin Liu, Liguo Wang, Danfeng Liu, Lei Fei, Jinghui Yang
Summary: This article proposes a non-parallel SVM model, which improves the classification effect and generalization performance for hyperspectral images by adding an additional empirical risk minimization term and bias constraint.
Article
Computer Science, Artificial Intelligence
Liming Liu, Maoxiang Chu, Rongfen Gong, Li Zhang
Summary: The improved nonparallel support vector machine (INPSVM) proposed in this article inherits the advantages of nonparallel support vector machine (NPSVM) while also offering incomparable benefits over twin support vector machine (TSVM). INPSVM effectively eliminates noise effects and achieves higher classification accuracy for both linear and nonlinear datasets compared to other algorithms. Experimental results demonstrate the superior efficiency, accuracy, and robustness of INPSVM.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Physics, Multidisciplinary
Li Xu, Xiao-Yu Zhang, Jin-Min Liang, Jing Wang, Ming Li, Ling Jian, Shu-qian Shen
Summary: Classical machine learning algorithms struggle with processing large amounts of data, while quantum machine learning algorithms offer exponential acceleration and are capable of handling big data. Variational quantum algorithms are commonly used to tackle computational problems on intermediate-scale quantum devices, and have shown superiority in quantum support vector machines with fewer qubits, shorter circuit depth, and simpler measurement requirements.
COMMUNICATIONS IN THEORETICAL PHYSICS
(2022)
Article
Computer Science, Artificial Intelligence
Bagesh Kumar, Ayush Sinha, Sourin Chakrabarti, O. P. Vyas
Summary: In this paper, a fast training method for OCSSVM is proposed, which enhances its scalability without compromising precision significantly. Experimental results show that the proposed method achieves the best tradeoff between training time and accuracy, providing similar accuracies to regular OCSSVM and better scalability compared to existing state-of-the-art one-class classifiers.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Neuroimaging
Ziqian Wang, Felix Dreyer, Friedemann Pulvermueller, Effrosyni Ntemou, Peter Vajkoczy, Lucius S. Fekonja, Thomas Picht
Summary: Our study utilized machine learning to analyze rTMS language mapping results in brain tumor patients, revealing a heightened sensitivity of the right inferior pars triangularis in patients with left perisylvian gliomas.
NEUROIMAGE-CLINICAL
(2021)
Article
Environmental Sciences
Teresa Salazar-Rojas, Fredy Ruben Cejudo-Ruiz, Guillermo Calvo-Brenes
Summary: This study establishes a method to predict heavy metal concentrations in leaves and road dust based on their magnetic properties measurements. Machine learning algorithms were used to establish prediction models, with support vector machine proving to be the most accurate. The results showed that the prediction models based on the magnetic properties of leaves yielded better results than those based on road dust and certain evergreen species.
ENVIRONMENTAL POLLUTION
(2022)
Article
Chemistry, Analytical
Tianhui Dong, Xueping Ma, Nan Sheng, Xiemin Qi, Yanan Chu, Qinxin Song, Bingjie Zou, Guohua Zhou
Summary: This study presents a fully automatic and contamination-free cassette system for nucleic acid detection, which can detect up to 10 targets in a sample with high accuracy and simplicity. The closed round design of the system allows for effective point-of-care genetic testing.
SENSORS AND ACTUATORS B-CHEMICAL
(2021)
Article
Computer Science, Artificial Intelligence
Chen Ding, Tian-Yi Bao, He-Liang Huang
Summary: The study proposes a quantum-inspired classical algorithm for LS-SVM, utilizing an improved sampling technique for classification. The theoretical analysis indicates that the algorithm can achieve classification with logarithmic runtime for low-rank, low-condition number, and high-dimensional data matrices.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Bikram Kumar, Deepak Gupta
Summary: The paper introduces a novel method ULTBSVM which utilizes Universum data to enhance the classification of healthy and seizure EEG signals, showing promising results in experiments.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Article
Biophysics
Luyang Wang, Xiaokun Wang, Lu Cheng, Shansen Ding, Guoqing Wang, Jaebum Choo, Lingxin Chen
Summary: SERS-based test strips, combining SERS technology, offer a powerful platform for ultrasensitive and multiplex detection of extensive analytes. Various strategies have been developed to improve the detection performance of SERS test strips for diagnosing disease biomarkers, nucleic acids, and toxins. This technology holds potential for future research directions.
BIOSENSORS & BIOELECTRONICS
(2021)
Review
Chemistry, Analytical
Jinchuan Yang, Kan Wang, Hao Xu, Wenqiang Yan, Qinghui Jin, Daxiang Cui
Article
Biochemical Research Methods
Kan Wang, Jinchuan Yang, Hao Xu, Bo Cao, Qi Qin, Xinmei Liao, Yan Wo, Qinghui Jin, Daxiang Cui
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2020)
Article
Biochemistry & Molecular Biology
Tobiloba Sojinrin, Kangze Liu, Kan Wang, Daxiang Cui, Hugh J. Byrne, James F. Curtin, Furong Tian
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2019)
Review
Biochemical Research Methods
Wei Zheng, Kan Wang, Hao Xu, Chujun Zheng, Bo Cao, Qi Qin, Qinghui Jin, Daxiang Cui
Summary: Microfluidic paper-based analytical devices (μPADs) have advantages such as small sample volume, rapid detection rates, low cost, and portability, making them suitable for various applications including food evaluation, disease screening, environmental monitoring, and drug testing. The devices employ detection methods like colorimetry, electrochemistry, chemiluminescence, electrochemiluminescence, and fluorescence-based methodologies. The choice of labeling material and design of microfluidic channels are crucial for detection results, and novel nanocomponents and smart structures have improved device performance.
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2021)
Review
Biochemical Research Methods
Yuemeng Cheng, Kan Wang, Hao Xu, Tangan Li, Qinghui Jin, Daxiang Cui
Summary: Wearable devices, with wearable sensors as functional components, have been widely used in medical and health applications, monitoring specific parameters and improving the quality and feasibility of medical treatment. By detecting human movement and maintaining high adaptability to the human body, wearable devices can evaluate body movement, monitor individual health status, evaluate environmental quality, and obtain more accurate environmental information. This review aims to provide insights and directions for the future development and broader application of wearable devices in various fields.
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2021)
Review
Biotechnology & Applied Microbiology
Tangan Li, Kan Wang, Chujun Zheng, Wei Zheng, Yuemeng Cheng, Qihong Ning, Hao Xu, Daxiang Cui
Summary: Nanomaterials, especially superparamagnetic nanomaterials, are playing essential roles in point-of-care testing due to their unique properties. Frequency mixing technology (FMT) is an emerging detection technique with high potential in biomedical quantitative detection. FMT sensors have advantages in robust, ultrasensitive biosensing but also face challenges in future development.
BIOTECHNOLOGY AND BIOENGINEERING
(2022)
Article
Biochemical Research Methods
Qihong Ning, Wei Zheng, Hao Xu, Armando Zhu, Tangan Li, Yuemeng Cheng, Shaoqing Feng, Li Wang, Daxiang Cui, Kan Wang
Summary: This paper presents the fabrication of multi-layer mu PADs for colorimetric detection of CRP using the imprinting method. The detection performance of mu PADs is improved through simulating different lighting conditions and shooting angles, and a machine learning algorithm is used for analysis. The results show that the YOLO model trained in this study can accurately identify all reaction areas, and the residual network algorithm achieves the highest accuracy in the classification task.
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2022)
Review
Chemistry, Analytical
Qihong Ning, Shaoqing Feng, Yuemeng Cheng, Tangan Li, Daxiang Cui, Kan Wang
Summary: This article explores the potential of electrochemical biosensors in real-time healthcare monitoring. It discusses the classification and comparison of commonly available electrochemical biosensors, and focuses on recent studies and applications. The article also identifies research gaps and proposes strategies for improvement, providing new guidelines for the advanced research and wider applications of electrochemical biosensors in in vitro diagnosis.
Article
Nanoscience & Nanotechnology
Yuemeng Cheng, Shaoqing Feng, Qihong Ning, Tangan Li, Hao Xu, Qingwen Sun, Daxiang Cui, Kan Wang
Summary: In this research, a small, convenient, and noninvasive paper-based microfluidic sweat sensor was designed and implemented to detect multiple key biomarkers in human sweat simultaneously. The chip's origami structure includes colorimetric and electrochemical sensing regions. Specific chromogenic reagents are used to selectively identify glucose, lactate, uric acid, magnesium ions, and the pH value in different colorimetric sensing regions. The cortisol in sweat is detected by molecular imprinting in the electrochemical sensing regions. The proposed sweat sensor, composed of hydrophilically and hydrophobically treated filter paper, and 3D microfluidic channels formed by folding paper, has been verified to reliably and noninvasively identify a variety of sweat biomarkers through on-body experiments.
MICROSYSTEMS & NANOENGINEERING
(2023)
Article
Biochemical Research Methods
Tangan Li, Chujun Zheng, Hao Xu, Qihong Ning, Qingwen Sun, Ruoyao Yu, Daxiang Cui, Kan Wang
Summary: This study optimized the sensor structure using mathematical physics modeling and finite element simulation to reduce signal interference and achieve multi-channel synchronous detection capability. The results showed that the optimized sensor can accurately identify adjacent samples with a smaller minimum spacing required.
BIOTECHNOLOGY JOURNAL
(2023)
Review
Chemistry, Multidisciplinary
Qingwen Sun, Qihong Ning, Tangan Li, Qixia Jiang, Shaoqing Feng, Ning Tang, Daxiang Cui, Kan Wang
Summary: This review explores methods to improve the sensitivity of SARS-CoV-2 detection through immunochromatography based on nanotechnology. It provides an overview of these methods and their performance, while addressing the challenges in COVID-19 diagnosis through lateral flow immunoassay.
Article
Chemistry, Analytical
Chujun Zheng, Qixia Jiang, Kan Wang, Tangan Li, Wei Zheng, Yuemeng Cheng, Qihong Ning, Daxiang Cui
Summary: In this study, a novel magnetic lateral flow assay was developed for dual-mode detection of gastrin-17 (G-17), an important biomarker for early gastric cancer diagnosis. The assay utilized iron oxide decorated with platinum probes, which exhibited magnetic properties and peroxidase activity. The assay showed high sensitivity and specificity, and results were consistent with the enzyme-linked immunosorbent assay method. The entire testing process was simple, rapid, and suitable for portable diagnostic applications.
Review
Chemistry, Analytical
Chujun Zheng, Kan Wang, Wei Zheng, Yuemeng Cheng, Tangan Li, Bo Cao, Qinghui Jin, Daxiang Cui
Summary: This review discusses two main research directions of lateral flow nucleic acid tests, one involving the incorporation of isothermal amplification methods for increased sensitivity, and the other focusing on the development of novel labeling materials for improved quantifiability. Future research will focus on integrating the entire testing process into microfluidic systems and combining with molecular diagnostic tools to facilitate rapid and accurate testing.
Review
Chemistry, Analytical
Qi Qin, Kan Wang, Jinchuan Yang, Hao Xu, Bo Cao, Yan Wo, Qinghui Jin, Daxiang Cui
