Search Results - "Machine Learning/classification"

Aprendizaje automático para clasificar pacientes infectados por COVID-19 sobre un conjunto de datos balanceado by Castillo, Carlos, Valdiviezo-Diaz, Priscila

“…Machine learning techniques can help identify infected patients, detect the spread of the virus, and analyze available patient information for better care and…”
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Classification of Human White Blood Cells Using Machine Learning for Stain‐Free Imaging Flow Cytometry by Lippeveld, Maxim, Knill, Carly, Ladlow, Emma, Fuller, Andrew, Michaelis, Louise J, Saeys, Yvan, Filby, Andrew, Peralta, Daniel

“…Imaging flow cytometry (IFC) produces up to 12 spectrally distinct, information‐rich images of single cells at a throughput of 5,000 cells per second. Yet…”
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Schizophrenia classification using machine learning on resting state EEG signal by Ruiz de Miras, J., Ibáñez-Molina, A.J., Soriano, M.F., Iglesias-Parro, S.

“…•Early diagnosis of schizophrenia is a very difficult task.•A processing pipeline for selecting features based on resting state EEG data is…”
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Adaptive transfer learning for EEG motor imagery classification with deep Convolutional Neural Network by Zhang, Kaishuo, Robinson, Neethu, Lee, Seong-Whan, Guan, Cuntai

“…In recent years, deep learning has emerged as a powerful tool for developing Brain–Computer Interface (BCI) systems. However, for deep learning models trained…”
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Digitized spiral drawing classification for Parkinson's disease diagnosis by Kamble, Megha, Shrivastava, Prashant, Jain, Megha

“…Parkinson's disease (PD) is the most common neurodegenerative disease affecting significantly motor functions of elderly persons. The diagnosis and monitoring…”
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Machine learning for clinical decision support in infectious diseases: a narrative review of current applications by Peiffer-Smadja, N, Rawson, T M, Ahmad, R, Buchard, A, Georgiou, P, Lescure, F-X, Birgand, G, Holmes, A H

“…Machine learning (ML) is a growing field in medicine. This narrative review describes the current body of literature on ML for clinical decision support in…”
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Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer by Parmar, Chintan, Grossmann, Patrick, Rietveld, Derek, Rietbergen, Michelle M., Lambin, Philippe, Aerts, Hugo J. W. L.

“…"Radiomics" extracts and mines a large number of medical imaging features in a non-invasive and cost-effective way. The underlying assumption of radiomics is…”
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Source tracking of antibiotic resistance genes in the environment — Challenges, progress, and prospects by Li, Li-Guan, Huang, Qi, Yin, Xiaole, Zhang, Tong

“…Antibiotic resistance has become a global public health concern, rendering common infections untreatable. Given the widespread occurrence, increasing attention…”
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Identification of autism spectrum disorder using deep learning and the ABIDE dataset by Heinsfeld, Anibal Sólon, Franco, Alexandre Rosa, Craddock, R. Cameron, Buchweitz, Augusto, Meneguzzi, Felipe

“…The goal of the present study was to apply deep learning algorithms to identify autism spectrum disorder (ASD) patients from large brain imaging dataset, based…”
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Machine learning classification of origins and varieties of Tetrastigma hemsleyanum using a dual-mode microscopic hyperspectral imager by Jiao, Changwei, Xu, Zhanpeng, Bian, Qiuwan, Forsberg, Erik, Tan, Qin, Peng, Xin, He, Sailing

“…[Display omitted] •A dual-mode microscopic hyperspectral imager (DMHI) was developed.•Machine learning was proposed for the classification of Tetrastigma…”
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Impact of Feature Choice on Machine Learning Classification of Fractional Anomalous Diffusion by Loch-Olszewska, Hanna, Szwabiński, Janusz

“…The growing interest in machine learning methods has raised the need for a careful study of their application to the experimental single-particle tracking…”
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Correction: Intelligent grading of sugarcane leaf disease severity by integrating physiological traits with the SSA-XGBoost algorithm by Wang, Xinrui, Sun, Jihong, Tian, Peng, Wu, Mengyao, Zhao, Jiawei, Chen, Jiangquan, Qian, Ye, Wang, Canyu

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Stimuli-induced modulation of white light emission in colloidal polymer particles: Design of chemosensors and dynamic chromism toward unclonable patterning and its classification based on machine learning by Mardani, Hanieh, Herizchi, Ata, Roghani-Mamaqani, Hossein

“…[Display omitted] •Synthesis of light-, pH-, and thermo-responsive colloidal polymer particles,•Stimuli-induced modulation of white light emission using FRET…”
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Health monitoring of CNC machining processes using machine learning and wavelet packet transform by Hussain, Abbas, Al Muhammadee Janjua, Taha, Naeem Malik, Anjum, Najib, Antash, Atta Khan, Shaheryar

“…Monitoring the health of a machining process plays a crucial role in advancing fully automated manufacturing. Faulty machining processes (abnormal process)…”
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Machine learning software to learn negligible elements of the Hamiltonian matrix by Qu, Chen, Houston, Paul L., Yu, Qi, Pandey, Priyanka, Conte, Riccardo, Nandi, Apurba, Bowman, Joel M.

“…As a follow-up to our recent Communication in the Journal of Chemical Physics [J. Chem. Phys. 159 071101 (2023)], we report and make available the Jupyter…”
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Functionally graded nanocomposite sensors for high-fidelity biomechanical monitoring by Jia, Xiaoli, Sun, Shilong, Miao, Yan, Liu, Lu, Ke, Liaoliang, Yang, Jie, Kitipornchai, Sritawat

“…Flexible pressure sensors are critical for next-generation wearable electronics and human-machine interfaces but remain constrained by trade-offs among gauge…”
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Extreme learning machine and adaptive sparse representation for image classification by Cao, Jiuwen, Zhang, Kai, Luo, Minxia, Yin, Chun, Lai, Xiaoping

“…Recent research has shown the speed advantage of extreme learning machine (ELM) and the accuracy advantage of sparse representation classification (SRC) in the…”
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Biomarkers for Alzheimer’s Disease in the Current State: A Narrative Review by Gunes, Serafettin, Aizawa, Yumi, Sugashi, Takuma, Sugimoto, Masahiro, Rodrigues, Pedro Pereira

“…Alzheimer’s disease (AD) has become a problem, owing to its high prevalence in an aging society with no treatment available after onset. However, early…”
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Named entity recognition in electronic health records using transfer learning bootstrapped Neural Networks by Gligic, Luka, Kormilitzin, Andrey, Goldberg, Paul, Nevado-Holgado, Alejo

“…Neural networks (NNs) have become the state of the art in many machine learning applications, such as image, sound (LeCun et al., 2015) and natural language…”
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Resting-state functional connectivity graph-properties correlate with bipolar disorder-risk in young medication-free depressed subjects by Cha, Jungwon, Spielberg, Jeffrey M., Hu, Bo, Altinay, Murat, Anand, Amit

“…•Network-based statistics using a resting state functional connectivity.•Performance of graph theory analysis with whole-brain graph properties.•Investigation…”
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