Výsledky vyhľadávania - Applied Machine Learning for Code Assessment

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

“… To overcome these limitations, previous work applied Machine-Learning that can learn from previous datasets without needing any threshold definition…”
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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.

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

“…), 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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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

“…Protein model quality assessment (QA) plays a very important role in protein structure prediction…”
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Development of a code-free machine learning model for the classification of cataract surgery phases Autor Touma, Samir, Antaki, Fares, Duval, Renaud

“…This study assessed the performance of automated machine learning (AutoML) in classifying cataract surgery phases from surgical videos…”
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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

“… (self-reported female sex) with breast cancer of any stage, comparing results from regression and machine learning…”
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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.

“… 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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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

“…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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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

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

“… This paper explores the use of the adaptive network-based fuzzy inference system (ANFIS), support vector machine (SVM…”
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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

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

“…Source code summarization refers to the natural language description of the source code’s function…”
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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

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

“… 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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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.

“… 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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Application of Machine Learning for Assessment of HS Code Correctness Autor Spichakova, Margarita, Haav, Hele-Mai

“… 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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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

“… (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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OP67 “Black Box Bottleneck” Paradigm And Transparency Issues On Artificial-Intelligence-Based Tools In Health Technology Assessment: A Scoping Review Autor Komoda, Denis Satoshi, de Almeida Cardoso, Marilia Mastrocolla, Lima, Ana Renata, Visacri, Marília Berlofa, Silveira Correa, Carlos Roberto, Fernandes, Brígida Dias

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Object-Oriented LULC Classification in Google Earth Engine Combining SNIC, GLCM, and Machine Learning Algorithms Autor Tassi, Andrea, Vizzari, Marco

“… (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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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

“… 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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