A Novel Approach for Blast-Induced Flyrock Prediction Based on Imperialist Competitive Algorithm and Artificial Neural Network by Aminaton Marto, Mohsen Hajihassani, Danial Jahed Armaghani, Edy Tonnizam Mohamad, Ahmad Mahir Makhtar

“…The scope of this study is to predict flyrock induced by blasting through a novel approach based on the combination of imperialist competitive algorithm (ICA) and artificial neural network (ANN). …”
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A novel strain-based bone-fracture healing algorithm is able to predict a range of healing outcomes by George T. Morgan, Lucas Low, Arul Ramasamy, Arul Ramasamy, Arul Ramasamy, Spyros D. Masouros

“…This study introduces a novel, strain-based fracture-healing algorithm designed to predict a wide range of healing outcomes, including both successful unions and non-unions. …”
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Predicting liver metastasis in pancreatic neuroendocrine tumors with an interpretable machine learning algorithm: a SEER-based study by Jinzhe Bi, Yaqun Yu

“…We applied 10 different machine learning algorithms to develop models for predicting the risk of liver metastasis in PaNETs patients. …”
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Energy Scheduling of Hydrogen Hybrid UAV Based on Model Predictive Control and Deep Deterministic Policy Gradient Algorithm by Haitao Li, Chenyu Wang, Shufu Yuan, Hui Zhu, Bo Li, Yuexin Liu, Li Sun

“…To overcome these limitations, this paper proposes a novel energy scheduling framework that integrates the Model Predictive Control (MPC) with a Deep Reinforcement Learning algorithm, specifically the Deep Deterministic Policy Gradient (DDPG). …”
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Presenting the AI models in predicting the settlement of earth dams using the results of spatiotemporal clustering and k-means algorithm by Behrang Beiranvand, Taher Rajaee, Mehdi Komasi

“…Therefore, the settlement location of the studied dam was determined using the results of the k-means clustering algorithm in the aforementioned AI models. The high accuracy of the results of the proposed method confirms the proper performance of using AI models in predicting and diagnosing the settlement of earthen dams using the results of k-means spatiotemporal clustering algorithm. …”
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Clean-Room Air Conditioning Control Based on Improved Min-Max Robust Model Predictive Control Algorithm by Qiang Luo, Ting Wang

“…The Min-Max robust model predictive control algorithm was 0.73 at the lowest and 4.3 at the highest. …”
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Implementation of Taguchi and Genetic Algorithm Techniques for Prediction of Optimal Part Dimensions for Polymeric Biocomposites in Fused Deposition Modeling by Raman Kumar, Jasgurpreet Singh Chohan, Sandeep Singh, Shubham Sharma, Yadvinder Singh, S. Rajkumar

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Evaluating GRU Algorithm and Double Moving Average for Predicting USDT Prices: A Case Study 2017-2024 by Rahmat Rizky, Munirul ula, Zara Yunizar

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Rapid and direct discovery of functional tumor specific neoantigens by high resolution mass spectrometry and novel algorithm prediction by Huajian Tian, Guifei Li, Cookson K.C. Chiu, E. Li, Yuzong Chen, Ting Zhu, Min Hu, Yanjie Wang, Suping Wen, Jiajia Li, Shuangxue Luo, Zhicheng Chen, Huimei Zeng, Nan Zheng, Jinyong Wang, Weijun Shen, Xi Kang

“…By combining this approach with our proprietary AI-based prediction algorithm and high-throughput in vitro functional validation, we can generate patient-specific neoantigen candidates within six weeks, accelerating personalized tumor vaccine development.…”
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Developing a predictive model for septic shock risk in acute pancreatitis patients using interpretable machine learning algorithms by Binglin Song, Ping Liu, Kangrui Fu, Chun Liu

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Predicting risky driving behavior with classification algorithms: results from a large-scale field-trial and simulator experiment by Thodoris Garefalakis, Eva Michelaraki, Stella Roussou, Christos Katrakazas, Tom Brijs, George Yannis

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Application of Gradient Boosting Machine Learning Algorithms to Predict Uniaxial Compressive Strength of Soft Sedimentary Rocks at Thar Coalfield by Niaz Muhammad Shahani, Muhammad Kamran, Xigui Zheng, Cancan Liu, Xiaowei Guo

“…Therefore, in this study, the XGBoost algorithm was shown to be the most accurate algorithm among all the investigated four algorithms for UCS prediction of soft sedimentary rocks of the Block-IX at Thar Coalfield, Pakistan.…”
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Leveraging Artificial Intelligence in Public Health: A Comparative Evaluation of Machine-Learning Algorithms in Predicting COVID-19 Mortality by Eric B. Weiser

“…Objective: This study aimed to evaluate and compare the predictive performance of four ML algorithms – K-Nearest Neighbors (KNN), Random Forest, Extreme Gradient Boosting (XGBoost), and Decision Tree – in estimating daily new COVID-19 deaths. …”
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How to use learning curves to evaluate the sample size for malaria prediction models developed using machine learning algorithms by Sophie G. Zaloumis, Megha Rajasekhar, Julie A. Simpson

“…Abstract Background Machine learning algorithms have been used to predict malaria risk and severity, identify immunity biomarkers for malaria vaccine candidates, and determine molecular biomarkers of antimalarial drug resistance. …”
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ADMET evaluation in drug discovery: 21. Application and industrial validation of machine learning algorithms for Caco-2 permeability prediction by Dong Wang, Jieyu Jin, Guqin Shi, Jingxiao Bao, Zheng Wang, Shimeng Li, Peichen Pan, Dan Li, Yu Kang, Tingjun Hou

“…Scientific contribution A comprehensive validation of various machine learning algorithms combined with diverse molecular representations on a large dataset for predicting Caco-2 permeability was reported. …”
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Predictive modeling of arginine vasopressin deficiency after transsphenoidal pituitary adenoma resection by using multiple machine learning algorithms by Yuyang Chen, Jiansheng Zhong, Haixiang Li, Kunzhe Lin, Liangfeng Wei, Shousen Wang

“…Abstract This study aimed to predict arginine vasopressin deficiency (AVP-D) following transsphenoidal pituitary adenoma surgery using machine learning algorithms. …”
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Improving Transformer Health Index Prediction Performance Using Machine Learning Algorithms with a Synthetic Minority Oversampling Technique by Muhammad Akmal A. Putra, Suwarno, Rahman Azis Prasojo

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Prediction of asthma outpatients using cumulative particulate matter and machine learning algorithms: a case study in Adiyaman, Turkey by Abdurrahman Özbeyaz, Mustafa Yıldırım, Fatih Tufaner

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Predictive Modeling of Yoga's Impact on Venous Clinical Severity Scoring Using Gaussian Process Classification and Advanced Optimization Algorithms by Yazdan Ashgevari, Faranak Kazemi

“…The study employs the Adaptive Opposition Slime Mould Algorithm (AOSM) and Mountain Gazelle Optimizer (MGO) to enhance the predictive capabilities of a Gaussian Process Classification (GPC) model. …”
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Development and validation of a biomarker-based prediction model for metastasis in patients with colorectal cancer: Application of machine learning algorithms by Erfan Ayubi, Sajjad Farashi, Leili Tapak, Saeid Afshar

“…The predictive performance of the algorithm with the highest accuracy was then externally validated on the GSE41568 dataset. …”
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