Výsledky vyhledávání - Applied Machine Learning for Code Assessment

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  1. 1

    A large empirical assessment of the role of data balancing in machine-learning-based code smell detection Autor Pecorelli, Fabiano, Di Nucci, Dario, De Roover, Coen, De Lucia, Andrea

    ISSN: 0164-1212
    Vydáno: Elsevier Inc 01.11.2020
    Vydáno v The Journal of systems and software (01.11.2020)
    “… To overcome these limitations, previous work applied Machine-Learning that can learn from previous datasets without needing any threshold definition…”
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    Journal Article
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    Can we screen for pancreatic cancer? Identifying a sub-population of patients at high risk of subsequent diagnosis using machine learning techniques applied to primary care data Autor Malhotra, Ananya, Rachet, Bernard, Bonaventure, Audrey, Pereira, Stephen P., Woods, Laura M.

    ISSN: 1932-6203, 1932-6203
    Vydáno: United States Public Library of Science 02.06.2021
    Vydáno v PloS one (02.06.2021)
    “…Pancreatic cancer (PC) represents a substantial public health burden. Pancreatic cancer patients have very low survival due to the difficulty of identifying…”
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    Journal Article
  3. 3

    How Good Is Your Verilog RTL Code? A Quick Answer from Machine Learning Autor Sengupta, Prianka, Tyagi, Aakash, Chen, Yiran, Hu, Jiang

    ISSN: 1558-2434
    Vydáno: ACM 29.10.2022
    “…), design iterations become prohibitively expensive. To this end, we propose a machine learning approach to Verilog-based Register-Transfer Level (RTL…”
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    Konferenční příspěvek
  4. 4

    QAcon: single model quality assessment using protein structural and contact information with machine learning techniques Autor Cao, Renzhi, Adhikari, Badri, Bhattacharya, Debswapna, Sun, Miao, Hou, Jie, Cheng, Jianlin

    ISSN: 1367-4803, 1367-4811
    Vydáno: England Oxford University Press 15.02.2017
    Vydáno v Bioinformatics (Oxford, England) (15.02.2017)
    “…Protein model quality assessment (QA) plays a very important role in protein structure prediction…”
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    Journal Article
  5. 5

    Development of a code-free machine learning model for the classification of cataract surgery phases Autor Touma, Samir, Antaki, Fares, Duval, Renaud

    ISSN: 2045-2322, 2045-2322
    Vydáno: London Nature Publishing Group UK 14.02.2022
    Vydáno v Scientific reports (14.02.2022)
    “…This study assessed the performance of automated machine learning (AutoML) in classifying cataract surgery phases from surgical videos…”
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    Journal Article
  6. 6

    Development and internal-external validation of statistical and machine learning models for breast cancer prognostication: cohort study Autor Clift, Ash Kieran, Dodwell, David, Lord, Simon, Petrou, Stavros, Brady, Michael, Collins, Gary S, Hippisley-Cox, Julia

    ISSN: 1756-1833, 1756-1833
    Vydáno: England British Medical Journal Publishing Group 10.05.2023
    Vydáno v BMJ (Online) (10.05.2023)
    “… (self-reported female sex) with breast cancer of any stage, comparing results from regression and machine learning…”
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    Journal Article
  7. 7

    Dense phenotyping from electronic health records enables machine learning-based prediction of preterm birth Autor Abraham, Abin, Le, Brian, Kosti, Idit, Straub, Peter, Velez-Edwards, Digna R., Davis, Lea K., Newton, J. M., Muglia, Louis J., Rokas, Antonis, Bejan, Cosmin A., Sirota, Marina, Capra, John A.

    ISSN: 1741-7015, 1741-7015
    Vydáno: London BioMed Central 28.09.2022
    Vydáno v BMC medicine (28.09.2022)
    “… Results We find that machine learning models based on billing codes alone can predict preterm birth risk at various gestational ages (e.g., ROC-AUC = 0.75, PR-AUC…”
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    Journal Article
  8. 8

    A deep learning solution for real-time quality assessment and control in additive manufacturing using point cloud data Autor Akhavan, Javid, Lyu, Jiaqi, Manoochehri, Souran

    ISSN: 0956-5515, 1572-8145
    Vydáno: New York Springer US 01.03.2024
    Vydáno v Journal of intelligent manufacturing (01.03.2024)
    “…This work presents an in-situ quality assessment and improvement technique using point cloud and AI for data processing and smart decision making in Additive Manufacturing (AM…”
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    Journal Article
  9. 9

    Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South Korea Autor Yu, Na Hyeon, Shin, Daeun, Ryu, Ik Hee, Yoo, Tae Keun, Koh, Kyungmin

    ISSN: 1472-6947, 1472-6947
    Vydáno: London BioMed Central 07.03.2025
    “…—are commonly utilized in clinical settings for disease risk assessment. This study aimed to develop a machine learning model to predict RVO risk in the general population…”
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    Journal Article
  10. 10

    Machine learning-assisted distinct element model calibration: ANFIS, SVM, GPR, and MARS approaches Autor Fathipour-Azar, Hadi

    ISSN: 1861-1125, 1861-1133
    Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2022
    Vydáno v Acta geotechnica (01.04.2022)
    “… This paper explores the use of the adaptive network-based fuzzy inference system (ANFIS), support vector machine (SVM…”
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    Journal Article
  11. 11

    Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art Autor Walia, Rasna R, Caragea, Cornelia, Lewis, Benjamin A, Towfic, Fadi, Terribilini, Michael, El-Manzalawy, Yasser, Dobbs, Drena, Honavar, Vasant

    ISSN: 1471-2105, 1471-2105
    Vydáno: London BioMed Central 10.05.2012
    Vydáno v BMC bioinformatics (10.05.2012)
    “… Understanding the molecular mechanisms by which proteins recognize and bind RNA is essential for comprehending the functional implications of these interactions, but the recognition ‘code…”
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    Journal Article
  12. 12

    A Survey of Automatic Source Code Summarization Autor Zhang, Chunyan, Wang, Junchao, Zhou, Qinglei, Xu, Ting, Tang, Ke, Gui, Hairen, Liu, Fudong

    ISSN: 2073-8994, 2073-8994
    Vydáno: Basel MDPI AG 01.03.2022
    Vydáno v Symmetry (Basel) (01.03.2022)
    “…Source code summarization refers to the natural language description of the source code’s function…”
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    Journal Article
  13. 13

    Assessment of punching shear strength of FRP-RC slab-column connections using machine learning algorithms Autor Truong, Gia Toai, Hwang, Hyeon-Jong, Kim, Chang-Soo

    ISSN: 0141-0296, 1873-7323
    Vydáno: Kidlington Elsevier Ltd 15.03.2022
    Vydáno v Engineering structures (15.03.2022)
    “… Recently, the use of fiber-reinforced polymer (FRP) bars replacing steel reinforcement has been widely applied to overcome the corrosion issue, particularly concrete slab-column connections using FRP bars as flexural reinforcement (FRP-RC slabs…”
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    Journal Article
  14. 14

    Seismic Impact on Building Structures: Assessment, Design, and Strengthening

    ISBN: 3725813612, 9783725813612, 3725813620, 9783725813629
    Vydáno: MDPI - Multidisciplinary Digital Publishing Institute 2024
    “… This Special Issue focuses on the structural impact of earthquakes on buildings. Original research and reviews covering structural modeling, vulnerability assessment…”
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    E-kniha
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    An empirical assessment of machine learning approaches for triaging reports of static analysis tools Autor Yerramreddy, Sai, Mordahl, Austin, Koc, Ugur, Wei, Shiyi, Foster, Jeffrey S., Carpuat, Marine, Porter, Adam A.

    ISSN: 1382-3256, 1573-7616
    Vydáno: New York Springer US 01.03.2023
    “… To improve the usability of these tools, researchers have recently begun to apply machine learning techniques to classify and filter incorrect analysis reports…”
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    Journal Article
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    Application of Machine Learning for Assessment of HS Code Correctness Autor Spichakova, Margarita, Haav, Hele-Mai

    ISSN: 2255-8950, 2255-8942, 2255-8950
    Vydáno: Riga University of Latvia 01.01.2020
    Vydáno v Baltic Journal of Modern Computing (01.01.2020)
    “… The paper provides an automated solution to this problem by applying machine learning methods to assess the correctness of Harmonized System codes…”
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    Journal Article
  17. 17

    Development and validation of ‘Patient Optimizer’ (POP) algorithms for predicting surgical risk with machine learning Autor Kowadlo, Gideon, Mittelberg, Yoel, Ghomlaghi, Milad, Stiglitz, Daniel K., Kishore, Kartik, Guha, Ranjan, Nazareth, Justin, Weinberg, Laurence

    ISSN: 1472-6947, 1472-6947
    Vydáno: London BioMed Central 11.03.2024
    “… (referred to as Patient Optimizer or POP) using Machine Learning (ML) that predict the development of post-operative complications and provide pilot data to inform the design of a larger prospective study…”
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    Journal Article
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    Object-Oriented LULC Classification in Google Earth Engine Combining SNIC, GLCM, and Machine Learning Algorithms Autor Tassi, Andrea, Vizzari, Marco

    ISSN: 2072-4292, 2072-4292
    Vydáno: Basel MDPI AG 17.11.2020
    Vydáno v Remote sensing (Basel, Switzerland) (17.11.2020)
    “… (OO) Land Use–Land Cover (LULC) classification approaches can be implemented, thanks to the availability of the many state-of-art functions comprising various Machine Learning (ML) algorithms…”
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    Journal Article
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    Exploiting generative self-supervised learning for the assessment of biological images with lack of annotations Autor Mascolini, Alessio, Cardamone, Dario, Ponzio, Francesco, Di Cataldo, Santa, Ficarra, Elisa

    ISSN: 1471-2105, 1471-2105
    Vydáno: London BioMed Central 24.07.2022
    Vydáno v BMC bioinformatics (24.07.2022)
    “… In this paper, we present Generative Adversarial Network Discriminator Learner (GAN-DL), a novel self-supervised learning paradigm based on the StyleGAN2 architecture…”
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    Journal Article