Suchergebnisse - Program Analysis for Machine Learning Models

Program Analysis for Machine Learning Models von Usman, Muhammad

“… Machine learning models have many applications, being used for example in pattern analysis, image classification, or sentiment analysis for textual data, and also in medical diagnosis or perception …”
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Artificial intelligence in dermatology: a comparative analysis of computer vision programs based on machine learning models von Korabelnikov, D. I., Lamotkin, A. I.

“… Objective: Comparative analysis of modern computer programs (smartphone programs …”
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Development of a machine-learning model to predict Gibbs free energy of binding for protein-ligand complexes von Bitencourt-Ferreira, Gabriela, de Azevedo, Walter Filgueira

“… From the computational view, the creation of reliable scoring functions is still an open problem in the simulation of biological systems, and the development of a new generation machine-learning …”
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INTERNATIONAL PATENT: KOMATSU LTD., 株式会社小松製作所 FILES APPLICATION FOR "ANALYSIS DEVICE, ANALYSIS METHOD, PROGRAM, LEARNED MACHINE LEARNING MODEL AND MACHINE LEARNING METHOD"

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The Impact of Crystallographic Data for the Development of Machine Learning Models to Predict Protein-Ligand Binding Affinity von Veit-Acosta, Martina, de Azevedo Junior, Walter Filgueira

“… Machine learning techniques can contribute to predicting this type of interaction. We may apply these techniques following two approaches …”
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Development of patient-specific apparent blood viscosity predictive models for computational fluid dynamics analysis of intracranial aneurysms with machine learning approaches von Suzuki, Takashi, Takao, Hiroyuki, Suzuki, Tomoaki, Fujimura, Soichiro, Hataoka, Shunsuke, Kodama, Tomonobu, Aoki, Ken, Ishibashi, Toshihiro, Yamamoto, Makoto, Yamamoto, Hideki, Murayama, Yuichi

“… •Predictive models for blood viscosity were constructed by machine learning.•Patient-specific viscosities were predicted from blood test results …”
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Identifying the Most Appropriate Intervention Targets Using Prediction Model Based on a Machine-Learning Method: A Retrospective Analysis of a Health Promotion Program for Improving Participation in General Health Check-Up von Shimoda, Akihiro, Saito, Yoshiyuki, Ooe, Chieko, Ichikawa, Daisuke, Igarashi, Ataru, Nakayama, Takeo, Saito, Toki, Oyama, Hiroshi

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INTERNATIONAL PATENT: VISA INTERNATIONAL SERVICE ASSOCIATION FILES APPLICATION FOR "METHOD, SYSTEM AND COMPUTER PROGRAM PRODUCT FOR ANALYSIS OF MACHINE LEARNING MODELS BASED ON SEQUENTIAL COUNTERFACTUAL ACTIONS"

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Probabilistic analysis of vertical concrete dry casks subjected to tip-over and aging effects von Ebad Sichani, Majid, Hanifehzadeh, Mohammad, Padgett, Jamie E., Gencturk, Bora

“… •Fragility and risk analysis is performed for the selected responses.•Effect of aging and variation of design parameters on the fragilities is explored …”
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Data-driven consideration of genetic disorders for global genomic newborn screening programs von Minten, Thomas, Bick, Sarah, Adelson, Sophia, Gehlenborg, Nils, Amendola, Laura M, Boemer, François, Coffey, Alison J, Encina, Nicolas, Ferlini, Alessandra, Kirschner, Janbernd, Russell, Bianca E, Servais, Laurent, Sund, Kristen L, Taft, Ryan J, Tsipouras, Petros, Zouk, Hana, Bick, David, Green, Robert C, Gold, Nina B

“… We used regression analysis to identify several predictors of inclusion and developed a machine learning model to rank genes for public health consideration …”
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Identifying Hydrilla verticillata in Real Time With a Machine Learning–Based Underwater Object Detection Program von Jeong, Han S., Schad, Aaron N., Cheng, Jing‐Ru C., Donohue, Griffin, Hawkins, Jazmine L., Steen, Andrew M., Farthing, William F., Knight, Ian A., Dodd, Lynde L., Katzenmeyer, Alan W., Sistrunk, Virginia A., Hammond, Shea L., Bellinger, Brent J., Rycroft, Taylor E.

“… To help with this challenge, we have developed an artificial intelligence/machine learning (AI/ML …”
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Machine learning for credit risk in the Reactive Peru Program: A comparison of the Lasso and Ridge Regression models von Geraldo-Campos, Luis Alberto, Soria, Juan J, Pando-Ezcurra, Tamara

“… This study aimed to determine the optimal machine learning predictive model for the credit risk of companies under the Reactiva Peru Program because of COVID-19 …”
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Efficient RTM-based training of machine learning regression algorithms to quantify biophysical & biochemical traits of agricultural crops von Danner, Martin, Berger, Katja, Wocher, Matthias, Mauser, Wolfram, Hank, Tobias

“… machine learning regression models fast and efficiently based on training data from a lookup table of synthetic vegetation …”
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Optimizing BenMAP health impact assessment with meteorological factor driven machine learning models von Wu, Juncheng, Dai, Qili, Song, Shaojie

“… ), caused by limited meteorological factor data and missing pollutant data. By employing data increment strategies and multiple machine learning models, this research …”
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Study on Process Design Based on Language Analysis and Image Discrimination Using CNN Deep Learning von Hayashi, Akio, Morimoto, Yoshitaka

“… At present, machining with numerically controlled (NC) machine tools is mostly performed by NC programs generated by computer-aided design and computer-aided manufacturing (CAD/CAM) systems …”
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Performance evaluation of machine learning models in cervical cancer diagnosis: Systematic review and meta-analysis von Ramos-Casallas, Alejandro, Cardona-Mendoza, Andrés, Perdomo-Lara, Sandra Janneth, Rico-Mendoza, Alejandro, Porras-Ramírez, Alexandra

“… This systematic review aimed to evaluate the diagnostic performance of machine learning models based on sociodemographic, epidemiologic, and clinical data for the detection of cervical cancer …”
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A general optimization framework for nanofabrication using shadow sphere Lithography: A case study on chiral nanohole arrays von Chen, Xinyi, Cheng, Mingyu, Zhang, Jinglan, Wang, Yuxia, Chen, Chong, Zhang, Qian, Zhang, Yongxin, Wang, Xingguo, Zhang, Gang, Ai, Bin

“… The approach combines a custom SSL program, a novel mathematical model for eliminating redundant structures, and machine learning (ML …”
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MLMD—A Malware-Detecting Antivirus Tool Based on the XGBoost Machine Learning Algorithm von Palša, Jakub, Ádám, Norbert, Hurtuk, Ján, Chovancová, Eva, Madoš, Branislav, Chovanec, Martin, Kocan, Stanislav

“… This paper focuses on training machine learning models using the XGBoost and extremely randomized trees algorithms on two datasets obtained using static and dynamic analysis of real malicious and benign samples …”
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Pan-cancer Transcriptomic Predictors of Perineural Invasion Improve Occult Histopathologic Detection von Guo, Jimmy A, Hoffman, Hannah I, Shroff, Stuti G, Chen, Peter, Hwang, Peter G, Kim, Daniel Y, Kim, Daniel W, Cheng, Stephanie W, Zhao, Daniel, Mahal, Brandon A, Alshalalfa, Mohammed, Niemierko, Andrzej, Wo, Jennifer Y, Loeffler, Jay S, Fernandez-Del Castillo, Carlos, Jacks, Tyler, Aguirre, Andrew J, Hong, Theodore S, Mino-Kenudson, Mari, Hwang, William L

“… Machine learning models were applied to build a PNI gene expression classifier. A blinded re-review of hematoxylin and eosin (H&E …”
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INTERNATIONAL PATENT: VISA INTERNATIONAL SERVICE ASSOCIATION FILES APPLICATION FOR "METHOD, SYSTEM AND COMPUTER PROGRAM PRODUCT FOR MULTI-LAYER ANALYSIS AND DETECTION OF VULNERABILITY OF MACHINE LEARNING MODELS TO ADVERSARIAL ATTACKS"

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