Human vs machine learning in face recognition: a case study from the travel industry by Regina Lionnie, Vidya Hermanto

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Controlling tangential flow filtration in biomanufacturing processes via machine learning: A literature review by Bastian Oetomo, Ling Luo, Yiran Qu, Michele Discepola, Sandra E. Kentish, Sally L. Gras

Subjects: “…Machine learning…”
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A Review on Optimizing Water Management in Agriculture through Smart Irrigation Systems and Machine Learning by Belarbi Zaid, El Younoussi Yacine

“…Recent advancements in machine learning (ML) offer promising alternatives to enhance the precision and efficiency of ET estimation and smart irrigation systems. …”
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Modeling PM2.5 Urban Pollution Using Machine Learning and Selected Meteorological Parameters by Jan Kleine Deters, Rasa Zalakeviciute, Mario Gonzalez, Yves Rybarczyk

“…The study demonstrates that the use of statistical models based on machine learning is relevant to predict PM2.5 concentrations from meteorological data.…”
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Machine Learning Classification Techniques for Detecting the Impact of Human Resources Outcomes on Commercial Banks Performance by Sulaiman O. Atiku, Ibidun C. Obagbuwa

“…Most researchers in the past adopted traditional statistics to build prediction models; however, due to the efficiency of machine learning algorithms, a lot of researchers now apply various machine learning algorithms to various fields, including performance prediction systems. …”
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Lost circulation intensity characterization in drilling operations: Leveraging machine learning and well log data by Ahmad Azadivash

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Functional gastrointestinal disorders predictors in neonates and toddlers: A machine learning approach to risk assessment by Flavia Indrio, Elio Masciari, Flavia Marchese, Matteo Rinaldi, Gianfranco Maffei, Ilaria Gangai, Assunta Grillo, Roberta De Benedetto, Enea Vincenzo Napolitano, Isadora Beghetti, Luigi Corvaglia, Antonio Di Mauro, Arianna Aceti

“…Conclusion: For the first time machine learning allowed to identify BW, cord blood pH and maternal age as important variable for risk prediction of FGIDs in the first year of life. …”
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Ab initio machine-learning unveils strong anharmonicity in non-Arrhenius self-diffusion of tungsten by Xi Zhang, Sergiy V. Divinski, Blazej Grabowski

“…With the aid of a bespoke machine-learning interatomic potential, the temperature-dependent vacancy formation and migration Gibbs energies of the prototype system body-centered cubic (BCC) tungsten are shown to be strongly affected by anharmonicity. …”
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New Media Marketing Strategy Optimization in the Catering Industry Based on Deep Machine Learning Algorithms by Zikang Peng

“…The communication module is connected with a deep machine learning algorithm system; that is, deep machine learning algorithm system is connected with a sales platform in communication. …”
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Diagnosis of invasive encapsulated follicular variant papillary thyroid carcinoma by protein-based machine learning by Truong Phan-Xuan Nguyen, Minh-Khang Le, Sittiruk Roytrakul, Shanop Shuangshoti, Nakarin Kitkumthorn, Somboon Keelawat

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Presentation of Machine Learning Approaches for Predicting the Severity of Accidents to Propose the Safety Solutions on Rural Roads by Mohammad Habibzadeh, Mahmoud Ameri, Hassan Ziari, Neda Kamboozia, Seyede Mojde Sadat Haghighi

“…In addition, both machine learning and statistical methods can be served as guidance for safety authorities to provide safety solutions, thereby leading to reducing accidents. …”
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Novel PCA-driven extreme machine learning for comprehensive modelling of metropolitan wastewater treatment systems by Vini Antony Grace N, Ghadah Aldehim, Nuha Alruwais, Prabakar T.N.

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On the development of diagnostic support algorithms based on CPET biosignals data via machine learning and wavelets by Rafael F. Pinheiro, Rui Fonseca-Pinto

“…Leveraging support vector machine (SVM) technology, a well-known machine learning classification method, in combination with wavelet transforms for feature extraction, the algorithm takes an innovative approach. …”
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Prediksi Kesiapan Sekolah Menggunakan Machine Learning Berbasis Kombinasi Adam dan Nesterov Momentum by Indah Mustika Rahayu, Ahmad Yusuf, Mujib Ridwan

“…Meanwhile, teachers and parents who have a role in providing support and stimulation to children cannot use these instrument. Machine learning is a technique that uses algorithms to find useful patterns in data. …”
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Prediction of acute kidney injury in intensive care unit patients based on interpretable machine learning by Li Zhang, Mingyu Li, Chengcheng Wang, Chi Zhang, Hong Wu

“…Predictive models were constructed using five machine learning algorithms based on MIMIC-IV data, and the best predictive model was selected by multiple model evaluation metrics. …”
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An interpretable machine learning model for predicting in-hospital mortality in ICU patients with ventilator-associated pneumonia. by Junying Wei, Heshan Cao, Mingling Peng, Yinzhou Zhang, Sibei Li, Wuhua Ma, Yuhui Li

“…This study aims to develop an interpretable machine learning (ML) prediction model to enhance the assessment of in-hospital mortality risk in VAP patients.…”
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Advanced Machine Learning to Predict Coronary Artery Disease Severity in Patients with Premature Myocardial Infarction by Yu-Hang Wang, Chang-Ping Li, Jing-Xian Wang, Zhuang Cui, Yu Zhou, An-Ran Jing, Miao-Miao Liang, Yin Liu, Jing Gao

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Environmental factors affecting the BMI of older adults in the Philippines spatially assessed using machine learning by D.K. Mendoza, A.B. Araza, L.D. Groot, M. Mensink, R.C. Tan

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Food Quality Inspection and Grading Using Efficient Image Segmentation and Machine Learning-Based System by V. Hemamalini, S. Rajarajeswari, S. Nachiyappan, M. Sambath, T. Devi, Bhupesh Kumar Singh, Abhishek Raghuvanshi

“…Then, fruit photos are classified using machine learning methods such as KNN, SVM, and C4.5. These algorithms determine if a fruit is damaged or not.…”
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Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector by A. Gavrikov, V. Cerrone, A. Serafini, R. Brugnera, A. Garfagnini, M. Grassi, B. Jelmini, L. Lastrucci, S. Aiello, G. Andronico, V. Antonelli, A. Barresi, D. Basilico, M. Beretta, A. Bergnoli, M. Borghesi, A. Brigatti, R. Bruno, A. Budano, B. Caccianiga, A. Cammi, R. Caruso, D. Chiesa, C. Clementi, S. Dusini, A. Fabbri, G. Felici, F. Ferraro, M.G. Giammarchi, N. Giudice, R.M. Guizzetti, N. Guardone, C. Landini, I. Lippi, S. Loffredo, L. Loi, P. Lombardi, C. Lombardo, F. Mantovani, S.M. Mari, A. Martini, L. Miramonti, M. Montuschi, M. Nastasi, D. Orestano, F. Ortica, A. Paoloni, E. Percalli, F. Petrucci, E. Previtali, G. Ranucci, A.C. Re, M. Redchuck, B. Ricci, A. Romani, P. Saggese, G. Sava, C. Sirignano, M. Sisti, L. Stanco, E. Stanescu Farilla, V. Strati, M.D.C. Torri, A. Triossi, C. Tuvè, C. Venettacci, G. Verde, L. Votano

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