Interpretable Machine Learning Insights into the Factors Influencing Residents’ Travel Distance Distribution by Rui Si, Yaoyu Lin, Dongquan Yang, Qijin Guo

“…Using travel distance data from ride-hailing services, this research divides a study area into 1 × 1 km grid cells, modeling the best travel distance distribution and calculating the coefficients of each grid. A machine learning framework (Extreme Gradient Boosting combined with Shapley Additive Explanations) is introduced to interpret the factors influencing these distributions. …”
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Retracted: Performance of Machine Learning and Image Processing in Plant Leaf Disease Detection by Journal of Food Quality

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Data Expression and Protection of Intellectual Property Education Resources Based on Machine Learning by Meng Mei, Hui Tan

“…The data expression and protection of intellectual property education resources based on machine learning is a kind of protection tool for the intellectual property of education resources developed using the characteristics of automation, real-time monitoring, and growth of machine learning. …”
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Spectral Analysis of Light-Adapted Electroretinograms in Neurodevelopmental Disorders: Classification with Machine Learning by Paul A. Constable, Javier O. Pinzon-Arenas, Luis Roberto Mercado Diaz, Irene O. Lee, Fernando Marmolejo-Ramos, Lynne Loh, Aleksei Zhdanov, Mikhail Kulyabin, Marek Brabec, David H. Skuse, Dorothy A. Thompson, Hugo Posada-Quintero

“…Standard time domain and signal analysis features were evaluated in different machine learning models. For ASD classification, a balanced accuracy (BA) of 0.87 was achieved for male participants. …”
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Review of Spot Electricity Price Prediction Studies Based on Machine Learning Methods by JIA Heping, GUO Yuchen, MA Qianxin, YANG Zhenglin, ZHENG Yaxian, ZENG Dan, LIU Dunnan

Subjects: “…national unified electricity market|spot market|electricity price forecasting|machine learning methods…”
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A Survey on Machine Learning Techniques for Head-Related Transfer Function Individualization by Davide Fantini, Michele Geronazzo, Federico Avanzini, Stavros Ntalampiras

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Implementing Machine Learning for Smart Farming to Forecast Farmers’ Interest in Hiring Equipment by Manik Rakhra, Sumaya Sanober, Noorulhasan Naveed Quadri, Neha Verma, Samrat Ray, Evans Asenso

“…In this research, three different machine learning models were utilized: nearest neighbors, logistic regression, and decision trees. …”
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A Deep Dive into a Groundbreaking Approach to Machine Learning-Powered E-Learning by Subhabrata Sengupta, Rupayan Das, Satyajit Chakrabarti

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A machine learning and clustering-based approach for county-level COVID-19 analysis. by Charles Nicholson, Lex Beattie, Matthew Beattie, Talayeh Razzaghi, Sixia Chen

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Integrating machine learning with mendelian randomization for unveiling causal gene networks in glioblastoma multiforme by Lixin Du, Pan Wang, Xiaoting Qiu, Zhigang Li, Jianlan Ma, Pengfei Chen

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Applications and challenges in designing VHH-based bispecific antibodies: leveraging machine learning solutions by Michael Mullin, James McClory, Winston Haynes, Justin Grace, Nathan Robertson, Gino van Heeke

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Multistage System-Based Machine Learning Techniques for Intrusion Detection in WiFi Network by Vu Viet Thang, F. F. Pashchenko

“…The aim of machine learning is to develop algorithms that can learn from data and solve specific problems in some context as human do. …”
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Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques. by Shayla Naznin, Md Jamal Uddin, Ishmam Ahmad, Ahmad Kabir

“…This study employs machine learning models, including Linear Regression, Ridge Regression, Lasso Regression, Bayesian Ridge, Decision Tree, Gradient Boosting, XGBoost, and CatBoost, to forecast future trends in under-5 mortality. …”
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E-Commerce Fraud Detection Based on Machine Learning Techniques: Systematic Literature Review by Abed Mutemi, Fernando Bacao

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Machine Learning and Artificial Intelligence Systems Based on the Optical Spectral Analysis in Neuro-Oncology by Tatiana Savelieva, Igor Romanishkin, Anuar Ospanov, Sergey Goryaynov, Galina Pavlova, Igor Pronin, Victor Loschenov

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Machine Learning-Based Offloading Strategy for Lightweight User Mobile Edge Computing Tasks by Shuchen Zhou, Waqas Jadoon, Junaid Shuja

“…This paper presents an in-depth study and analysis of offloading strategies for lightweight user mobile edge computing tasks using a machine learning approach. Firstly, a scheme for multiuser frequency division multiplexing approach in mobile edge computing offloading is proposed, and a mixed-integer nonlinear optimization model for energy consumption minimization is developed. …”
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Application of machine learning in diabetes prediction based on electronic health record data analysis by Yang Zihan

“…With the application of electronic health records (EHRs) in the medical field, the use of machine learning to predict disease has become one of the important research hotspots in the healthcare industry. …”
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Building occupancy type classification and uncertainty estimation using machine learning and open data by Tom Narock, J. Michael Johnson, Justin Singh-Mohudpur, Arash Modaresi Rad

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Machine Learning Does Not Improve Humeral Torsion Prediction Compared to Regression in Baseball Pitchers by Garrett S Bullock, Charles A Thigpen, Gary S Collins, Nigel K Arden, Thomas K Noonan, Michael J Kissenberth, Ellen Shanley

“…While machine learning models demonstrated improved RMSE compared to the regression, the machine learning models displayed poorer calibration compared to regression. …”
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Artificial intelligence and machine learning in mobile apps for mental health: A scoping review. by Madison Milne-Ives, Emma Selby, Becky Inkster, Ching Lam, Edward Meinert

“…PubMed was systematically searched for randomised controlled trials and cohort studies published in English since 2014 that evaluate artificial intelligence- or machine learning-enabled mobile apps for mental health support. …”
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