Comparing Statistical and Machine Learning Methods for Time Series Forecasting in Data-Driven Logistics—A Simulation Study by Lena Schmid, Moritz Roidl, Alice Kirchheim, Markus Pauly

Subjects: “…machine learning…”
Get full text

Machine learning prediction of obesity-associated gut microbiota: identifying Bifidobacterium pseudocatenulatum as a potential therapeutic target by Hao Wu, Yuan Li, Yuxuan Jiang, Xinran Li, Shenglan Wang, Changle Zhao, Changle Zhao, Ximiao Yang, Baocheng Chang, Juhong Yang, Juhong Yang, Jianjun Qiao, Jianjun Qiao

Subjects: Get full text

Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME by Md. Manowarul Islam, Habibur Rahman Rifat, Md. Shamim Bin Shahid, Arnisha Akhter, Md Ashraf Uddin, Khandaker Mohammad Mohi Uddin

Subjects: Get full text

Development and external validation of machine learning-based models to predict patients with cellulitis developing sepsis during hospitalisation by Li Hu, Xilingyuan Chen, Rentao Yu

“…This study was designed to develop and compare different models for predicting patients with cellulitis developing sepsis during hospitalisation.Design This is a retrospective cohort study.Setting This study included both the development and the external-validation phases from two independent large cohorts internationally.Participants and methods A total of 6695 patients with cellulitis in the Medical Information Mart for Intensive care (MIMIC)-IV database were used to develop models with different machine-learning algorithms. The best models were selected and then externally validated in 2506 patients with cellulitis from the YiduCloud database of our university. …”
Get full text

Assessing the diagnostic accuracy of machine learning algorithms for identification of asthma in United States adults based on NHANES dataset by Omid Kohandel Gargari, Mobina Fathi, Shahryar Rajai Firouzabadi, Ida Mohammadi, Mohammad Hossein Mahmoudi, Mehran Sarmadi, Arman Shafiee

Subjects: Get full text

Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches by Nafiseh Hosseini, Hamid Tanzadehpanah, Amin Mansoori, Mostafa Sabzekar, Gordon A. Ferns, Habibollah Esmaily, Majid Ghayour-Mobarhan

Get full text

Retracted: Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning by Journal of Food Quality

Get full text

Computer Aided Diagnostic System for Blood Cells in Smear Images Using Texture Features and Supervised Machine Learning by Shakhawan Hares Wady

Subjects: “…Leukaemia diagnosis; blood smear; feature extraction; machine learning…”
Get full text

Multi-omic and machine learning analysis of mitochondrial RNA modification genes in lung adenocarcinoma for prognostic and therapeutic implications by Xiao Zhang, Jiatao Liu, Yaolin Cao, Wei Wang, Haoran Lin, Yue Yu

Subjects: Get full text

Ensemble machine learning models for lung cancer incidence risk prediction in the elderly: a retrospective longitudinal study by Songjing Chen, Sizhu Wu

Subjects: Get full text

Enhancing Soil Moisture Prediction in Drought-Prone Agricultural Regions Using Remote Sensing and Machine Learning Approaches by Xizhuoma Zha, Shaofeng Jia, Yan Han, Wenbin Zhu, Aifeng Lv

“…The results indicated that the machine learning model achieved a correlation coefficient (R) of 0.92 for estimating spatial near-surface soil moisture. …”
Get full text

Vegetation height estimation based on machine learning model driven by multi-source data in Eurasian temperate grassland by Wuhua Wang, Jiakui Tang, Na Zhang, Xuefeng Xu, Anan Zhang, Yanjiao Wang, Kaihui Li, Yidan Wang

Subjects: Get full text

Comparative analysis of Sentinel-2 and PlanetScope imagery for chlorophyll-a prediction using machine learning models by Eden T. Wasehun, Leila Hashemi Beni, Courtney A. Di Vittorio, Christopher M. Zarzar, Kyana R.L. Young

“…Consequently, spatiotemporal maps of Chl-a concentration across the reservoir were generated using the best-performing machine learning models: XGBoost for S2 data and SVR for PS data. …”
Get full text

Assessing chemical exposure risk in breastfeeding infants: An explainable machine learning model for human milk transfer prediction by Xiaojie Huang, Jiajia Chen, Peineng Liu

Subjects: Get full text

A data driven machine learning approach for predicting and optimizing sulfur compound adsorption on metal organic frameworks by Mohsen Shayanmehr, Sepehr Aarabi, Ahad Ghaemi, Alireza Hemmati

Subjects: Get full text

Predicting the reduction in heatstroke and heart disease-related mortality under urban modification scenarios using machine learning by Yukitaka Ohashi, Ko Nakajima, Yuya Takane, Yukihiro Kikegawa, Tomohiko Ihara, Kazutaka Oka

Subjects: Get full text

Oscillating Mindfully: Using Machine Learning to Characterize Systems-Level Electrophysiological Activity During Focused Attention Meditation by Noga Aviad, Oz Moskovich, Ophir Orenstein, Etam Benger, Arnaud Delorme, Amit Bernstein

Subjects: Get full text

Predictive Power of Machine Learning for Optimizing Solar Water Heater Performance: The Potential Application of High-Throughput Screening by Hao Li, Zhijian Liu, Kejun Liu, Zhien Zhang

“…Fortunately, knowledge-based machine learning can provide a fast and precise prediction method for SWH performance. …”
Get full text

All-Cause Mortality Prediction in Subjects with Diabetes Mellitus Using a Machine Learning Model and Shapley Values by Oana Mirea, Mostafa Ghelich Oghli, Oana Neagoe, Mihaela Berceanu, Eugen Țieranu, Liviu Moraru, Victor Raicea, Ionuț Donoiu

Subjects: Get full text

Data-Driven Machine-Learning Model in District Heating System for Heat Load Prediction: A Comparison Study by Fisnik Dalipi, Sule Yildirim Yayilgan, Alemayehu Gebremedhin

“…We present our data-driven supervised machine-learning (ML) model to predict heat load for buildings in a district heating system (DHS). …”
Get full text