Support-vector networks

Cited by (1,254)

Items 1,101–1,200 of 1,254

1. Disease Prediction via Graph Neural Networks
   Sun, Zhenchao, Yin, Hongzhi, Chen, Hongxu, Chen, Tong, Cui, Lizhen, Yang, Fan · 2021 · IEEE Journal of Biomedical and Health Informatics
2. Real-Time Event-Driven Classification Technique for Early Detection and Prevention of Myocardial Infarction on Wearable Systems
   Sopic, Dionisije, Aminifar, Amin, Aminifar, Amir, Atienza, David · 2018 · IEEE Transactions on Biomedical Circuits and Systems
3. Radiologically Defined Ecological Dynamics and Clinical Outcomes in Glioblastoma Multiforme: Preliminary Results
   Zhou, Mu, Hall, Lawrence, Goldgof, Dmitry, Russo, Robin, Balagurunathan, Yoganand, Gillies, Robert, Gatenby, Robert · 2014 · Translational Oncology
4. Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms
   AlQuraishi, Mohammed, Sorger, Peter K. · 2021 · Nature Methods
5. SuRVoS: Super-Region Volume Segmentation workbench
   Luengo, Imanol, Darrow, Michele C., Spink, Matthew C., Sun, Ying, Dai, Wei, He, Cynthia Y., Chiu, Wah, Pridmore, Tony, Ashton, Alun W., Duke, Elizabeth M.H. et al. · 2017 · Journal of Structural Biology
6. Optimizing prediction of response to antidepressant medications using machine learning and integrated genetic, clinical, and demographic data
   Taliaz, Dekel, Spinrad, Amit, Barzilay, Ran, Barnett-Itzhaki, Zohar, Averbuch, Dana, Teltsh, Omri, Schurr, Roy, Darki-Morag, Sne, Lerer, Bernard · 2021 · Translational Psychiatry
7. APRIL: Active Preference Learning-Based Reinforcement Learning
   Akrour, Riad, Schoenauer, Marc, Sebag, Michèle · 2012 · Lecture Notes in Computer Science
8. A topological approach for protein classification
   Cang, Zixuan, Mu, Lin, Wu, Kedi, Opron, Kristopher, Xia, Kelin, Wei, Guo-Wei · 2015 · Computational and Mathematical Biophysics
9. Machine learning stability and band gap of lead-free halide double perovskite materials for perovskite solar cells
   Guo, Zongmei, Lin, Bin · 2021 · Solar Energy
10. An overview of the prediction of protein DNA-binding sites
    Si, Jingna, Zhao, Rui, Wu, Rongling · 2015 · International Journal of Molecular Sciences
11. On the Existence of Simpler Machine Learning Models
    Semenova, Lesia, Rudin, Cynthia, Parr, Ronald · 2022 · 2022 ACM Conference on Fairness Accountability and Transparency
12. Predicting treatment response to antidepressant medication using early changes in emotional processing
    Browning, Michael, Kingslake, Jonathan, Dourish, Colin T., Goodwin, Guy M., Harmer, Catherine J, Dawson, Gerard R. · 2019 · European Neuropsychopharmacology
13. Decision trees do not generalize to new variations
    Bengio, Yoshua, Delalleau, Olivier, Simard, Clarence · 2010 · Computational Intelligence
14. A new approach for oil tank detection using deep learning features with control false alarm rate in high-resolution satellite imagery
    Zalpour, Moein, Akbarizadeh, Gholamreza, Alaei-Sheini, Navid · 2020 · International Journal of Remote Sensing
15. Statistical workflow for feature selection in human metabolomics data
    Antonelli, Joseph, Claggett, Brian L., Henglin, Mir, Kim, Andy, Ovsak, Gavin, Kim, Nicole, Deng, Katherine, Rao, Kevin, Tyagi, Octavia, Watrous, Jeramie D. et al. · 2019 · Metabolites
16. Automated defect detection for Fluorescent Penetrant Inspection using Random Forest
    Shipway, N.J., Barden, T.J., Huthwaite, P., Lowe, M.J.S. · 2019 · NDT & E International
17. Encoding of predictable and unpredictable stimuli by inferior temporal cortical neurons
    Kumar, Susheel, Kaposvari, Peter, Vogels, Rufin · 2017 · Journal of Cognitive Neuroscience
18. Using Convolutional Neural Networks to Automate Aircraft Maintenance Visual Inspection
    Dogru, Anil, Bouarfa, Soufiane, Arizar, Ridwan, Aydogan, Reyhan · 2020
19. Classifiers and their Metrics Quantified
    Brown, J. B. · 2018 · Molecular Informatics
20. Finding better active learners for faster literature reviews
    Yu, Zhe, Kraft, Nicholas A., Menzies, Tim · 2018 · Empirical Software Engineering
21. Artificial intelligence facilitates drug design in the big data era
    Wang, Liangliang, Ding, Junjie, Pan, Li, Cao, Dongsheng, Jiang, Hui, Ding, Xiaoqin · 2019 · Chemometrics and Intelligent Laboratory Systems
22. “Hasta la vista, baby” – will machine learning terminate human literature reviews in entrepreneurship?
    Robledo, Sebastian, Grisales Aguirre, Andrés Mauricio, Hughes, Mathew, Eggers, Fabian · 2023 · Journal of Small Business Management
23. Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity
    Zhang, J D, Berntenis, N, Roth, A, Ebeling, M · 2014 · The Pharmacogenomics Journal
24. Automated assessment of patients’ self-narratives for posttraumatic stress disorder screening using natural language processing and text mining
    He, Qiwei, Veldkamp, Bernard P., Glas, Cees A. W., de Vries, Theo · 2017 · Assessment
25. Speech based detection of Alzheimer's disease: a survey of AI techniques, datasets and challenges
    Ding, Kewen, Chetty, Madhu, Noori Hoshyar, Azadeh, Bhattacharya, Tanusri, Klein, Britt · 2024 · Artificial Intelligence Review
26. MACE prediction of acute coronary syndrome via boosted resampling classification using electronic medical records
    Huang, Zhengxing, Chan, Tak-Ming, Dong, Wei · 2017 · Journal of Biomedical Informatics
27. Machine learning-based prediction for settling velocity of microplastics with various shapes
    Qian, Shangtuo, Qiao, Xuyang, Zhang, Wenming, Yu, Zijian, Dong, Shunan, Feng, Jiangang · 2024 · Water Research
28. A multifaceted vision of the human-AI collaboration: a comprehensive review
    Puerta-Beldarrain, Maite, Gómez-Carmona, Oihane, Sánchez-Corcuera, Rubén, Casado-Mansilla, Diego, López-de-Ipiña, Diego, Chen, Liming · 2025 · IEEE Access
29. micro-Stress EMA: A Passive Sensing Framework for Detecting in-the-wild Stress in Pregnant Mothers
    King, Zachary D., Moskowitz, Judith, Egilmez, Begum, Zhang, Shibo, Zhang, Lida, Bass, Michael, Rogers, John, Ghaffari, Roozbeh, Wakschlag, Laurie, Alshurafa, Nabil · 2019 · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
30. A review of recent advances and strategies in transfer learning
    Gholizade, Masoume, Soltanizadeh, Hadi, Rahmanimanesh, Mohammad, Sana, Shib Sankar · 2025 · International Journal of System Assurance Engineering and Management
31. Parkinson’s disease and essential tremor classification on mobile device
    Woods, Alan Michael, Nowostawski, Mariusz, Franz, Elizabeth A., Purvis, Martin · 2014 · Pervasive and Mobile Computing
32. Machine Learning in Human Olfactory Research
    Lötsch, Jörn, Kringel, Dario, Hummel, Thomas · 2019 · Chemical Senses
33. A Random Sampling Technique for Training Support Vector Machines: For Primal-Form Maximal-Margin Classifiers
    Balcázar, Jose, Dai, Yang, Watanabe, Osamu · 2001 · Lecture Notes in Computer Science
34. Spatial prediction of demersal fish diversity in the Baltic Sea: comparison of machine learning and regression-based techniques
    Smoliński, Szymon, Radtke, Krzysztof · 2017 · ICES Journal of Marine Science
35. Based on the network degeneration hypothesis: Separating individual patients with different neurodegenerative syndromes in a preliminary hybrid PET/MR study
    Tahmasian, Masoud, Shao, Junming, Meng, Chun, Grimmer, Timo, Diehl-Schmid, Janine, Yousefi, Behrooz H., Förster, Stefan, Riedl, Valentin, Drzezga, Alexander, Sorg, Christian · 2016 · Journal of Nuclear Medicine
36. Data analysis with Shapley values for automatic subject selection in Alzheimer’s disease data sets using interpretable machine learning
    Bloch, Louise, Friedrich, Christoph M., for the Alzheimer’s Disease Neuroimaging Initiative · 2021 · Alzheimer's Research & Therapy
37. Study on feature selection methods for depression detection using three-electrode EEG data
    Cai, Hanshu, Chen, Yunfei, Han, Jiashuo, Zhang, Xiangzi, Hu, Bin · 2018 · Interdisciplinary Sciences: Computational Life Sciences
38. Classification of defects in steel strip surface based on multiclass support vector machine
    Hu, Huijun, Li, Yuanxiang, Liu, Maofu, Liang, Wenhao · 2014 · Multimedia Tools and Applications
39. A multiple combined method for rebalancing medical data with class imbalances
    Wang, Yun-Chun, Cheng, Ching-Hsue · 2021 · Computers in Biology and Medicine
40. A survey on outlier explanations
    Panjei, Egawati, Gruenwald, Le, Leal, Eleazar, Nguyen, Christopher, Silvia, Shejuti · 2022 · The VLDB Journal
41. ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia
    Laengsri, V., Shoombuatong, W., Adirojananon, W., Nantasenamat, C., Prachayasittikul, V., Nuchnoi, P. · 2019 · BMC Medical Informatics and Decision Making
42. Solving Inefficiency of Self-supervised Representation Learning
    Wang, Guangrun, Wang, Keze, Wang, Guangcong, Torr, Philip H.S., Lin, Liang · 2021 · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
43. An incremental method combining density clustering and support vector machines for voice pathology detection
    Amami, Rimah, Smiti, Abir · 2017 · Computers & Electrical Engineering
44. Imputing Phenotypes for Genome-wide Association Studies
    Hormozdiari, Farhad, Kang, Eun Yong, Bilow, Michael, Ben-David, Eyal, Vulpe, Chris, McLachlan, Stela, Lusis, Aldons J., Han, Buhm, Eskin, Eleazar · 2016 · The American Journal of Human Genetics
45. Machine learning in materials design: Algorithm and application*
    Song, Zhilong, Chen, Xiwen, Meng, Fanbin, Cheng, Guanjian, Wang, Chen, Sun, Zhongti, Yin, Wan-Jian · 2020 · Chinese Physics B
46. Equivariant Graph Neural Networks for Toxicity Prediction
    Cremer, Julian, Medrano Sandonas, Leonardo, Tkatchenko, Alexandre, Clevert, Djork-Arné, De Fabritiis, Gianni · 2023 · Chemical Research in Toxicology
47. Machine learning based soft sensor model for BOD estimation using intelligence at edge
    Pattnaik, Bhawani Shankar, Pattanayak, Arunima Sambhuta, Udgata, Siba Kumar, Panda, Ajit Kumar · 2021 · Complex & Intelligent Systems
48. Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach
    Beaudouin, Valérie, Bloch, Isabelle, Bounie, David, Clémençon, Stéphan, d'Alché-Buc, Florence, Eagan, James, Maxwell, Winston, Mozharovskyi, Pavlo, Parekh, Jayneel · 2020 · SSRN Electronic Journal
49. Prediction of heat waves over Pakistan using support vector machine algorithm in the context of climate change
    Khan, Najeebullah, Shahid, Shamsuddin, Ismail, Tarmizi Bin, Behlil, Farida · 2021 · Stochastic Environmental Research and Risk Assessment
50. A hybrid heuristic-based tuned support vector regression model for cloud load prediction
    Barati, Masoud, Sharifian, Saeed · 2015 · The Journal of Supercomputing
51. Identifying and analyzing different cancer subtypes using RNA-seq data of blood platelets
    Zhang, Yu-Hang, Huang, Tao, Chen, Lei, Xu, YaoChen, Hu, Yu, Hu, Lan-Dian, Cai, Yudong, Kong, Xiangyin · 2017 · Oncotarget
52. Multimodal mild depression recognition based on EEG-EM synchronization acquisition network
    Zhu, Jing, Wang, Ying, La, Rong, Zhan, Jiawei, Niu, Junhong, Zeng, Shuai, Hu, Xiping · 2019 · IEEE Access
53. Deploying nEmesis: Preventing Foodborne Illness by Data Mining Social Media
    Sadilek, Adam, Kautz, Henry, DiPrete, Lauren, Labus, Brian, Portman, Eric, Teitel, Jack, Silenzio, Vincent · 2017 · AI Magazine
54. Machine learning models for predicting the activity of AChE and BACE1 dual inhibitors for the treatment of Alzheimer’s disease
    Dhamodharan, G., Mohan, C. Gopi · 2022 · Molecular Diversity
55. Application of Shearlet transform to classification of surface defects for metals
    Xu, Ke, Liu, Shunhua, Ai, Yonghao · 2015 · Image and Vision Computing
56. Discovering foodborne illness in online restaurant reviews
    Effland, Thomas, Lawson, Anna, Balter, Sharon, Devinney, Katelynn, Reddy, Vasudha, Waechter, HaeNa, Gravano, Luis, Hsu, Daniel · 2018 · Journal of the American Medical Informatics Association
57. An evolutionary classifier for steel surface defects with small sample set
    Xiao, Mang, Jiang, Mingming, Li, Guangyao, Xie, Li, Yi, Li · 2017 · EURASIP Journal on Image and Video Processing
58. Measuring Patient Mobility in the ICU Using a Novel Noninvasive Sensor
    Ma, Andy J., Rawat, Nishi, Reiter, Austin, Shrock, Christine, Zhan, Andong, Stone, Alex, Rabiee, Anahita, Griffin, Stephanie, Needham, Dale M., Saria, Suchi · 2017 · Critical Care Medicine
59. Decomposition Methods for Linear Support Vector Machines
    Kao, Wei-Chun, Chung, Kai-Min, Sun, Chia-Liang, Lin, Chih-Jen · 2004 · Neural Computation
60. Process knowledge based multi-class support vector classification (PK-MSVM) approach for surface defects in hot rolling
    Agarwal, Kuldeep, Shivpuri, Rajiv, Zhu, Yijun, Chang, Tzyy-Shuh, Huang, Howard · 2011 · Expert Systems with Applications
61. Human Activity Recognition Data Analysis: History, Evolutions, and New Trends
    Ariza-Colpas, Paola Patricia, Vicario, Enrico, Oviedo-Carrascal, Ana Isabel, Butt Aziz, Shariq, Piñeres-Melo, Marlon Alberto, Quintero-Linero, Alejandra, Patara, Fulvio · 2022 · Sensors
62. Natural language processing: using artificial intelligence to understand human language in orthopedics
    Pruneski, James A., Pareek, Ayoosh, Nwachukwu, Benedict U., Martin, R. Kyle, Kelly, Bryan T., Karlsson, Jón, Pearle, Andrew D., Kiapour, Ata M., Williams, Riley J. · 2023 · Knee Surgery, Sports Traumatology, Arthroscopy
63. Relevance Vector Machines: Sparse Classification Methods for QSAR
    Burden, Frank R., Winkler, David A. · 2015 · Journal of Chemical Information and Modeling
64. Applying machine learning to estimate the optical properties of black carbon fractal aggregates
    Luo, Jie, Zhang, Yongming, Wang, Feng, Wang, Jinjun, Zhang, Qixing · 2018 · Journal of Quantitative Spectroscopy and Radiative Transfer
65. Analyzing high speed rail passengers’ train choices based on new online booking data in China
    Sun, Yanshuo, Jiang, Zhibin, Gu, Jinjing, Zhou, Min, Li, Yeming, Zhang, Lei · 2018 · Transportation Research Part C: Emerging Technologies
66. Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM
    Zhang, Chaolong, He, Yigang, Yuan, Lifeng, Xiang, Sheng, Wang, Jinping · 2015 · Computational Intelligence and Neuroscience
67. Automated Emerging Cyber Threat Identification and Profiling Based on Natural Language Processing
    Marinho, Renato, Holanda, Raimir · 2023 · IEEE Access
68. Automatic Subtyping of Individuals with Primary Progressive Aphasia
    Themistocleous, Charalambos, Ficek, Bronte, Webster, Kimberly, den Ouden, Dirk-Bart, Hillis, Argye E., Tsapkini, Kyrana · 2021 · Journal of Alzheimer’s Disease
69. Fully automated 2D–3D registration and verification
    Varnavas, Andreas, Carrell, Tom, Penney, Graeme · 2015 · Medical Image Analysis
70. Functional dissociation between anterior temporal lobe and inferior frontal gyrus in the processing of dynamic body expressions: Insights from behavioral variant frontotemporal dementia
    Jastorff, Jan, De Winter, Francois‐Laurent, Van den Stock, Jan, Vandenberghe, Rik, Giese, Martin A., Vandenbulcke, Mathieu · 2016 · Human Brain Mapping
71. Application of a semi-automated vocal fingerprinting approach to monitor Bornean gibbon females in an experimentally fragmented landscape in Sabah, Malaysia
    Clink, Dena J., Crofoot, Margaret C., Marshall, Andrew J. · 2019 · Bioacoustics
72. An Algorithm for Surface Defect Identification of Steel Plates Based on Genetic Algorithm and Extreme Learning Machine
    Tian, Siyang, Xu, Ke · 2017 · Metals
73. A machine learning approach to QoE-based video admission control and resource allocation in wireless systems
    Testolin, Alberto, Zanforlin, Marco, De Filippo De Grazia, Michele, Munaretto, Daniele, Zanella, Andrea, Zorzi, Marco, Zorzi, Michele · 2014 · 2014 13th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET)
74. Complex Networks Govern Coiled-Coil Oligomerization – Predicting and Profiling by Means of a Machine Learning Approach
    Mahrenholz, Carsten C., Abfalter, Ingrid G., Bodenhofer, Ulrich, Volkmer, Rudolf, Hochreiter, Sepp · 2011 · Molecular & Cellular Proteomics
75. Probabilistic medical predictions of large language models
    Gu, Bowen, Desai, Rishi J., Lin, Kueiyu Joshua, Yang, Jie · 2024 · npj Digital Medicine
76. Steel surface defect classification using multiple hyper-spheres support vector machine with additional information
    Gong, Rongfen, Wu, Chengdong, Chu, Maoxiang · 2018 · Chemometrics and Intelligent Laboratory Systems
77. Support vector machine classification of Parkinson’s disease and essential tremor subjects based on temporal fluctuation
    Surangsrirat, Decho, Thanawattano, Chusak, Pongthornseri, Ronachai, Dumnin, Songphon, Anan, Chanawat, Bhidayasiri, Roongroj · 2016 · 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
78. Infants’ neural speech discrimination predicts individual differences in grammar ability at 6 years of age and their risk of developing speech-language disorders
    Zhao, T. Christina, Boorom, Olivia, Kuhl, Patricia K., Gordon, Reyna · 2021 · Developmental Cognitive Neuroscience
79. Part of speech production in patients with primary progressive aphasia: An analysis based on natural language processing
    Themistocleous, Charalambos, Webster, Kimberly, Afthinos, Alexandros, Tsapkini, Kyrana · 2021 · American Journal of Speech-Language Pathology
80. The Dream Catcher experiment: blinded analyses failed to detect markers of dreaming consciousness in EEG spectral power
    Wong, William, Noreika, Valdas, Móró, Levente, Revonsuo, Antti, Windt, Jennifer, Valli, Katja, Tsuchiya, Naotsugu · 2020 · Neuroscience of Consciousness
81. ADLAuth: Passive Authentication Based on Activity of Daily Living Using Heterogeneous Sensing in Smart Cities
    Malik, Maryam Naseer, Azam, Muhammad Awais, Ehatisham-Ul-Haq, Muhammad, Ejaz, Waleed, Khalid, Asra · 2019 · Sensors
82. Automatic classification of literature in systematic reviews on food safety using machine learning
    van den Bulk, Leonieke M., Bouzembrak, Yamine, Gavai, Anand, Liu, Ningjing, van den Heuvel, Lukas J., Marvin, Hans J.P. · 2022 · Current Research in Food Science
83. MindLink-Eumpy: An Open-Source Python Toolbox for Multimodal Emotion Recognition
    Li, Ruixin, Liang, Yan, Liu, Xiaojian, Wang, Bingbing, Huang, Wenxin, Cai, Zhaoxin, Ye, Yaoguang, Qiu, Lina, Pan, Jiahui · 2021 · Frontiers in Human Neuroscience
84. Machine learning techniques for the automation of literature reviews and systematic reviews in EFSA
    Jaspers, Stijn, De Troyer, Ewoud, Aerts, Marc · 2018 · EFSA Supporting Publications
85. Battery SOH estimation based on decision tree and improved support vector machine regression algorithm
    Qian, Lijun, Xuan, Liang, Chen, Jian · 2023 · Frontiers in Energy Research
86. Combining explainable machine learning, demographic and multi-omic data to inform precision medicine strategies for inflammatory bowel disease
    Gardiner, Laura-Jayne, Carrieri, Anna Paola, Bingham, Karen, Macluskie, Graeme, Bunton, David, McNeil, Marian, Pyzer-Knapp, Edward O. · 2022 · PLOS ONE
87. Machine learning predictive outcomes modeling in inflammatory bowel diseases
    Javaid, Aamir, Shahab, Omer, Adorno, William, Fernandes, Philip, May, Eve, Syed, Sana · 2022 · Inflammatory Bowel Diseases
88. A Novel Multiresolution-Statistical Texture Analysis Architecture: Radiomics-Aided Diagnosis of PDAC Based on Plain CT Images
    Qiu, Jia-Jun, Yin, Jin, Qian, Wei, Liu, Jin-Heng, Huang, Zi-Xing, Yu, Hao-Peng, Ji, Lin, Zeng, Xiao-Xi · 2021 · IEEE Transactions on Medical Imaging
89. DNN is not all you need: Parallelizing Non-Neural ML Algorithms on Ultra-Low-Power IoT Processors
    Tabanelli, Enrico, Tagliavini, Giuseppe, Benini, Luca · 2021 · arXiv
90. An Equivalence between the Lasso and Support Vector Machines
    Jaggi, Martin · 2013 · arXiv
91. ToxCast EPA <i>in Vitro</i> to <i>in Vivo</i> Challenge: Insight into the Rank-I Model
    Novotarskyi, Sergii, Abdelaziz, Ahmed, Sushko, Yurii, Körner, Robert, Vogt, Joachim, Tetko, Igor V. · 2016 · Chemical Research in Toxicology
92. Evaluating Real-Life Performance of Lithium-Ion Battery Packs in Electric Vehicles
    Klass, Verena, Behm, Mårten, Lindbergh, Göran · 2012 · Journal of The Electrochemical Society
93. Advanced analytics for the automation of medical systematic reviews
    Timsina, Prem, Liu, Jun, El-Gayar, Omar · 2016 · Information Systems Frontiers
94. Unraveling city-specific signature and identifying sample origin locations for the data from CAMDA MetaSUB challenge
    Zhang, Runzhi, Walker, Alejandro R., Datta, Susmita · 2021 · Biology Direct
95. Towards Long-term Non-invasive Monitoring for Epilepsy via Wearable EEG Devices
    Ingolfsson, Thorir Mar, Cossettini, Andrea, Wang, Xiaying, Tabanelli, Enrico, Tagliavini, Giuseppe, Ryvlin, Philippe, Benini, Luca, Benatti, Simone · 2021 · 2021 IEEE Biomedical Circuits and Systems Conference (BioCAS)
96. Anomaly Analysis of Alzheimer’s Disease in PET Images Using an Unsupervised Adversarial Deep Learning Model
    Baydargil, Husnu Baris, Park, Jang-Sik, Kang, Do-Young · 2021 · Applied Sciences
97. Integrated multi-class classification and prediction of GPCR allosteric modulators by machine learning intelligence
    Hou, Tianling, Bian, Yuemin, McGuire, Terence, Xie, Xiang-Qun · 2021 · Biomolecules
98. Predicting winning and losing businesses when changing electricity tariffs
    Granell, Ramon, Axon, Colin J., Wallom, David C.H. · 2014 · Applied Energy
99. An Evaluation of the Effectiveness of Image-based Texture Features Extracted from Static B-mode Ultrasound Images in Distinguishing between Benign and Malignant Ovarian Masses
    Al-karawi, Dhurgham, Al-Assam, Hisham, Du, Hongbo, Sayasneh, Ahmad, Landolfo, Chiara, Timmerman, Dirk, Bourne, Tom, Jassim, Sabah · 2021 · Ultrasonic Imaging
100. vTC: Machine Learning Based Traffic Classification as a Virtual Network Function
     He, Lu, Xu, Chen, Luo, Yan · 2016 · Proceedings of the 2016 ACM International Workshop on Security in Software Defined Networks &amp; Network Function Virtualization