Development of a prediction model for acute respiratory distress syndrome in ICU patients with acute pancreatitis based on machine learning algorithms by REN Xia*，LIU Luojie，ZHA Junjie，YE Ye，XU Xiaodan，YE Hongwei，ZHANG Yan

“…"Objective To develop and validate a predictive model based on machine learning algorithms to assess the risk of acute respiratory distress syndrome（ARDS）in patients with acute pancreatitis（AP）admitted to the intensive care unit（ICU）. …”
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Prediction of Treatment Recommendations Via Ensemble Machine Learning Algorithms for Non-Small Cell Lung Cancer Patients in Personalized Medicine by Hojin Moon, Lauren Tran, Andrew Lee, Taeksoo Kwon, Minho Lee

“…Objectives: The primary goal of this research is to develop treatment-related genomic predictive markers for non-small cell lung cancer by integrating various machine learning algorithms that recommends near-optimal individualized patient treatment for chemotherapy in an effort to maximize efficacy or minimize treatment-related toxicity. …”
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Machine learning algorithms predict breast cancer incidence risk: a data-driven retrospective study based on biochemical biomarkers by Qianqian Guo, Peng Wu, Junhao He, Ge Zhang, Wu Zhou, Qianjun Chen

“…Furthermore, the six machine learning algorithms consistently identified GGT and ALT as the most significant predictive features. …”
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Construction of a risk prediction model for postoperative deep vein thrombosis in colorectal cancer patients based on machine learning algorithms by Xin Liu, Xingming Shu, Yejiang Zhou, Yifan Jiang

“…Moreover, the SHAP method identified age and preoperative prealbumin as the primary determinants influencing ML model predictions. Finally, the study employed LIME for more precise prediction and interpretation of individual predictions.ConclusionThe machine learning algorithms effectively predicted postoperative lower limb deep vein thrombosis in colorectal cancer patients. …”
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Application of machine learning algorithms for predicting the life-long physiological effects of zinc oxide Micro/Nano particles on Carum copticum by Maryam Mazaheri-Tirani, Soleyman Dayani, Majid Iranpour Mobarakeh

“…All levels of ZnO NPs treatments increased growth parameters compared to the control. All ML algorithms showed varied efficiencies in predicting the nonlinear relationships among parameters, with higher efficiency in predicting the behavior of root and shoot dry mass, root fresh weight and number of flowers according to R2 index. …”
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Analyzing Agricultural Land Price Prediction Using Linear Regression and XGBoost Machine Learning Algorithms: A Case Study of Çanakkale by Simge Doğan, Levent Genç, Sait Can Yücebaş, Metin Uşaklı

“…This study aims to compare the MLR and XGBoost algorithms to predict agricultural land prices in villages located in the central district of Çanakkale and to examine daily fluctuations in economic indicators such as the dollar, gold, and euro. …”
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Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics by Simona Ruxandra Volovăț, Tudor Ovidiu Popa, Dragoș Rusu, Lăcrămioara Ochiuz, Decebal Vasincu, Maricel Agop, Călin Gheorghe Buzea, Cristian Constantin Volovăț

“…Traditional machine learning (ML) algorithms have been widely used for this purpose; however, recent advancements in deep learning, such as autoencoders, offer the potential to enhance predictive accuracy. …”
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Improve carbon dioxide emission prediction in the Asia and Oceania (OECD): nature-inspired optimisation algorithms versus conventional machine learning by Loke Kok Foong, Vojtech Blazek, Lukas Prokop, Stanislav Misak, Farruh Atamurotov, Nima Khalilpoor

“…Future research should explore additional optimisation algorithms and ensemble techniques to improve prediction robustness and accuracy. …”
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Toward prediction of entrepreneurial exit in Iran; a study based on GEM 2008-2019 data and approach of machine learning algorithms by Masoumeh Moterased, Seyed Mojtaba Sajadi, Ali Davari, Mohammad Reza Zali

“…This research applies the Random Forest Algorithm to get a prediction model that shows the entrepreneurial exit. …”
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Optimizing Equivalent Property-Damage-Only (EPDO) Prediction Models with Genetic Algorithms: A Case Study on Roundabout Geometric Characteristics by Hossein Samadi, Omid Rahmani, Khaled Shaaban, Amir Saman Abdollahzadeh Nasiri, Mehrzad Hasanvand

Subjects: “…crash prediction model…”
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Development and Internal Validation of Machine Learning Algorithms for Predicting Subsequent Contralateral Slipped Capital Femoral Epiphysis in Patients With Unilateral Slips by David P. VanEenenaam, Jr., BS, Carter Hall, BS, Daniel A. Maranho, MD, PhD, Christopher J. DeFrancesco, MD, Eduardo N. Novais, MD, Wudbhav N. Sankar, MD

“…Machine learning (ML) algorithms can be leveraged to identify complex, nonlinear patterns in data and allow for more accurate predictions on which patients may need a prophylactic pin. …”
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Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk by Mohamed Chaouch, Omama M. Al-Hamed

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Transformer–BiLSTM Fusion Neural Network for Short-Term PV Output Prediction Based on NRBO Algorithm and VMD by Xiaowei Fan, Ruimiao Wang, Yi Yang, Jingang Wang

“…And finally, the VMD-NRBO-Transformer-BiLSTM prediction model and hyperparameter selection are evaluated by the NRBO algorithm. …”
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Prediction of Chlorophyll-a Concentration Distribution Using Generative Adversarial Network (GAN) Algorithm on Processed Remote Sensing Images by Wattaqwa Amira Zul’Ilmi, Jaya Indra, Iqbal Muhammad

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A Meta-Heuristic Algorithm-Based Feature Selection Approach to Improve Prediction Success for Salmonella Occurrence in Agricultural Waters by Murat Canayaz, Murat Demir, Zeynal Topalcengiz

“…Recently, the performances of various algorithms have been tested for the prediction of indicator bacteria population and pathogen occurrence in agricultural water sources. …”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…Optuna's tree-structured Parzen estimator (TPE) and pruning algorithms are employed to generate more precise estimates of soil nutrients. …”
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Applying genetic algorithm to extreme learning machine in prediction of tumbler index with principal component analysis for iron ore sintering by Senhui Wang

“…The results showed that an improvement in predictive accuracy can be obtained by the GA-ELM approach, and the accuracy of TI prediction is 81.85% for absolute error under 0.7%.…”
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Prediction of train wheel diameter based on Gaussian process regression optimized using a fast simulated annealing algorithm. by Xiaoying Yu, Hongsheng Su, Zeyuan Fan, Yu Dong

“…The results predicted by FSA-GPR was compared with other three algorithms as well as the real measured data from RMSE, MAE, R2 and Residual value. …”
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Prediction of Crop Yield by Support Vector Machine Coupled with Deep Learning Algorithm Procedures in Lower Kulfo Watershed of Ethiopia by Abebe Temesgen Ayalew, Tarun Kumar Lohani

“…Sensible and judicious utilization of water for agriculture in conjunction with prediction techniques increases the crop yield. The Ethiopian economy relies on and is exclusively dependent on agricultural-based activities. …”
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A Sensor Data Prediction and Early-Warning Method for Coal Mining Faces Based on the MTGNN-Bayesian-IF-DBSCAN Algorithm by Mingyang Liu, Xiaodong Wang, Wei Qiao, Hongbo Shang, Zhenguo Yan, Zhixin Qin

“…Experimental results indicate that the MTGNN outperforms comparative algorithms, such as CrossGNN and FourierGNN, in prediction accuracy, with the mean absolute error (MAE) being as low as 0.00237 and the root mean square error (RMSE) maintained below 0.0203 across different sensor locations (T0, T1, T2). …”
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