A Collection of Machine Learning Models for Improved Airport Operations Amidst Adverse Weather Conditions by Ramon Dalmau, Jonathan Attia

Subjects: “…Machine Learning…”
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Improving molecular subtypes and prognosis of pancreatic cancer through multi group analysis and machine learning by Xue-Jian Zhang, Fang-Fang Lin, Ya-Qing Wen, Kun-Ping Guan

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Biodegradation of CAHs and BTEX in groundwater at a multi-polluted pesticide site undergoing natural attenuation: Insights from identifying key bioindicators using machine learning... by Feiyang Xia, Tingting Fan, Mengjie Wang, Lu Yang, Da Ding, Jing Wei, Yan Zhou, Dengdeng Jiang, Shaopo Deng

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A Review of Environmental Perception Technology Based on Multi-Sensor Information Fusion in Autonomous Driving by Boquan Yang, Jixiong Li, Ting Zeng

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SYMBOLIC ANALYSIS OF CLASSICAL NEURAL NETWORKS FOR DEEP LEARNING by Vladimir Milićević, Igor Franc, Maja Lutovac Banduka, Nemanja Zdravković, Nikola Dimitrijević

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A Comparative Study of Anomaly Detection Techniques for IoT Security Using Adaptive Machine Learning for IoT Threats by Dheyaaldin Alsalman

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DESIGN OF TRANSLATION AMBIGUITY ELIMINATION METHOD BASED ON RECURRENT NEURAL NETWORKS by Jianzhou Cui

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Enhancing Monkeypox Detection through Data Analytics: A Comparative Study of Machine and Deep Learning Techniques by Kinjal A. Patel, Asadi Srinivasulu, Kuntesh Jani, Goddindla Sreenivasulu

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Conquering myositis, beyond remission by Amber O'Connor, T G Sundaram

Subjects: “…international business machines…”
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Stochasticity as a solution for overfitting—A new model and comparative study on non-invasive EEG prospects by Yousef A. Radwan, Eslam Ahmed Mohamed, Donia Metwalli, Mariam Barakat, Anas Ahmed, Antony E. Kiroles, Sahar Selim

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Artificial Intelligence-Powered Materials Science by Xiaopeng Bai, Xingcai Zhang

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Machine learning models for predicting the bearing capacity of shallow foundations: A Comparative study and sensitivity analysis by Hamid Mohammadnezhad, Seyedmohammad Eslami

Subjects: “…machine learning…”
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Machine learning for classifying chronic kidney disease and predicting creatinine levels using at-home measurements by Brady Metherall, Anna K. Berryman, Georgia S. Brennan

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Comprehensive Analysis of Programmed Cell Death-Related Genes in Diagnosis and Synovitis During Osteoarthritis Development: Based on Bulk and Single-Cell RNA Sequencing Data by Zhou J, Jiao S, Huang J, Dai T, Xu Y, Xia D, Feng Z, Chen J, Li Z, Hu L, Meng Q

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Diabetes and Cataracts Development—Characteristics, Subtypes and Predictive Modeling Using Machine Learning in Romanian Patients: A Cross-Sectional Study by Adriana Ivanescu, Simona Popescu, Adina Braha, Bogdan Timar, Teodora Sorescu, Sandra Lazar, Romulus Timar, Laura Gaita

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Determining university’s readiness to implement AI technologies for personalizing educational paths by V. S. Starostin, K. A. Arzhanova, D. V. Dolgopolov, A. D. Ditrikh

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Effect of Feature Selection on the Prediction of Direct Normal Irradiance by Mohamed Khalifa Boutahir, Yousef Farhaoui, Mourade Azrour, Imad Zeroual, Ahmad El Allaoui

Subjects: “…machine learning…”
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Machine learning insights into early mortality risks for small cell lung cancer patients post-chemotherapy by Min Liang, Min Liang, Fuyuan Luo

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Modeling the determinants of attrition in a two-stage epilepsy prevalence survey in Nairobi using machine learning by Daniel M. Mwanga, Isaac C. Kipchirchir, George O. Muhua, Charles R. Newton, Damazo T. Kadengye, Abankwah Junior, Albert Akpalu, Arjune Sen, Bruno Mmbando, Charles R. Newton, Cynthia Sottie, Dan Bhwana, Daniel Mtai Mwanga, Damazo T. Kadengye, Daniel Nana Yaw, David McDaid, Dorcas Muli, Emmanuel Darkwa, Frederick Murunga Wekesah, Gershim Asiki, Gergana Manolova, Guillaume Pages, Helen Cross, Henrika Kimambo, Isolide S. Massawe, Josemir W. Sander, Mary Bitta, Mercy Atieno, Neerja Chowdhary, Patrick Adjei, Peter O. Otieno, Ryan Wagner, Richard Walker, Sabina Asiamah, Samuel Iddi, Simone Grassi, Sloan Mahone, Sonia Vallentin, Stella Waruingi, Symon Kariuki, Tarun Dua, Thomas Kwasa, Timothy Denison, Tony Godi, Vivian Mushi, William Matuja

Subjects: “…Machine learning…”
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Harnessing Machine Learning and Nomogram Models to Aid in Predicting Progression-Free Survival for Gastric Cancer Patients Post-Gastrectomy with Deficient Mismatch Repair(dMMR) by Yifan Li, JinFeng Ma, Wenhua Cheng

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