Fruit Orchard Canopy Recognition and Extraction of Characteristics Based on Millimeter-Wave Radar by Yinlong Jiang, Jieli Duan, Yang Li, Jiaxiang Yu, Zhou Yang, Xing Xu

“…The average relative errors of crown width, plant height, and volume were 2.1%, 2.3%, and 4.2%, respectively, indicating that the spray had little effect on the extraction of canopy characteristics by millimeter-wave radar, which could inform spray-related decisions for precise applications.…”
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Assessing of a Radiation Therapy Sessionʼs Duration at the Stage of Pre-Radiation Preparation by M. N. Piatkevich, E. V. Titovich

“…The treatment planning process includes a review of the radiation treatment plan which leads to a decision on the patientʼs treatment technique. The scope of this study was to create a mathematical model for calculating of a radiation therapy session duration during the pre-radiation planning stage.For dosimetric planning of radiation treatment the authors provided a formula and an algorithm for determining of a patientʼs irradiation session duration. …”
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AI-Driven predicting and optimizing lignocellulosic sisal fiber-reinforced lightweight foamed concrete: A machine learning and metaheuristic approach for sustainable construction by Mohamed Sahraoui, Aissa Laouissi, Yacine Karmi, Abderazek Hammoudi, Mostefa Hani, Yazid Chetbani, Ahmed Belaadi, Ibrahim M.H. Alshaikh, Djamel Ghernaout

“…Six predictive models were assessed for accuracy and generalization: Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbor (KNN), Linear Model (LM), Dragonfly Algorithm-based Deep Neural Network (DNN-DA), and Improved Grey Wolf Optimizer-based Deep Neural Network (DNN-IGWO). …”
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Microservice Deployment Based on Multiple Controllers for User Response Time Reduction in Edge-Native Computing by Zhaoyang Wang, Jinqi Zhu, Jia Guo, Yang Liu

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A Reinforcement Learning Model for Optimal Treatment Strategies in Intensive Care: Assessment of the Role of Cardiorespiratory Features by Cristian Drudi, Maximiliano Mollura, Li-wei H. Lehman, Riccardo Barbieri

“…We selected patients meeting the Sepsis-3 criteria from the Multi-parameter Intelligent Monitoring in Intensive Care (MIMIC III) database, resulting in a total of 20,496 ICU admissions. …”
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Evaluation of a Machine Learning Model Based on Laboratory Parameters for the Prediction of Influenza A and B in Chongqing, China: Multicenter Model Development and Validation Stud... by Weiwei Hu, Yulong Liu, Jian Dong, Xuelian Peng, Chunyan Yang, Honglin Wang, Yong Chen, Shan Shi, Jin Li

“…The CatBoost (CATB) algorithm was optimized via 5-fold cross-validation and random grid search using 24 routine blood parameters. …”
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5-Fluorouracil Toxicity: Revisiting the Relevance of Pharmacokinetic Parameters by Hans Mielke, Engi Abd Elhady Algharably, Ursula Gundert-Remy

“…Data analysis supported by a decision algorithm suggests that the 5-FU steady-state plasma concentration is a better toxicity predictor than the AUC. …”
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Building trust for traffic flow forecasting components in intelligent transportation systems via interpretable ensemble learning by Jishun Ou, Jingyuan Li, Chen Wang, Yun Wang, Qinghui Nie

“…However, most existing studies have concentrated on developing advanced algorithms or models to attain state-of-the-art forecasting accuracy. …”
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Subtyping Service Receipt in Personality Disorder Services in South London: Observational Validation Study Using Latent Profile Analysis by Jack Steadman, Rob Saunders, Mark Freestone, Robert Stewart

“…ConclusionsThese results suggest that routinely collected data may be used to classify likely engagement subtypes among patients with complex needs. The algorithm identified factors associated with service use and has the potential to inform clinical decision-making to improve treatment for individuals with complex needs.…”
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Multivariate forecasting of dengue infection in Bangladesh: evaluating the influence of data downscaling on machine learning predictive accuracy by Mahadee Al Mobin

“…Leveraging a robust data pipeline, this research incorporates a strategic downscaling technique, applying the Stochastic Bayesian Downscaling (SBD) algorithm to convert monthly DENV case data to daily frequency. …”
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A Novel Semi-Supervised Method for Predicting Remanufacturing Costs of Used Electromechanical Devices Using Quality Characteristics by Junying Hu, Huan Xu, Ke Zhang

“…Remanufacturing cost is a key factor for making decisions on the remanufacturing of used electromechanical devices in the construction sector. …”
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Application Analysis of Credit Scoring of Financial Institutions Based on Machine Learning Model by Yi Wu, Yuwen Pan

“…Due to the high dimension of personal credit data, the pdC-RF algorithm is adopted in this paper to optimize the correlation of data features and reduce the 145-dimensional data to 22-dimensional data. …”
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Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response by Zhichun Yang, Lin Cheng, Huaidong Min, Yang Lei, Yanfeng Yang

“…Uncertainties from RES generation and load demand are addressed through an ambiguity set, enabling robust decision-making. The column-and-constraint generation (C&CG) algorithm efficiently solves the two-stage DRO model. …”
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Development and validation of a small-sample machine learning model to predict 5–year overall survival in patients with hepatocellular carcinoma by Tingting Jiang, Xingyu Liu, Wencan He, Hepei Li, Xiang Yan, Qian Yu, Shanjun Mao

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Interpretable multiparametric MRI radiomics-based machine learning model for preoperative differentiation between benign and malignant prostate masses: a diagnostic, multicenter st... by Wenjun Zhou, Wenjun Zhou, Zhangcheng Liu, Zhangcheng Liu, Jindong Zhang, Shuai Su, Yu Luo, Lincen Jiang, Kun Han, Guohua Huang, Jue Wang, Jianhua Lan, Delin Wang

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Toward improving precision and complexity of transformer-based cost-sensitive learning models for plant disease detection by Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Oscal Tzyh-Chiang Chen, Oscal Tzyh-Chiang Chen

“…This study introduces an automated system for early disease detection in plants that enhanced a lightweight model based on the robust machine learning algorithm. In particular, we introduced a transformer module, a fusion of the SPP and C3TR modules, to synthesize features in various sizes and handle uneven input image sizes. …”
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Cost-effectiveness of advanced hepatic fibrosis screening in individuals with suspected MASLD identified by serologic noninvasive tests by Huiyul Park, Eileen L. Yoon, Mimi Kim, Ji-hyeon Park, Ramsey Cheung, Jeong-Yeon Cho, Hye-Lin Kim, Dae Won Jun

“…Implementing a two-step screening algorithm for advanced hepatic fibrosis in patients with suspected MASLD based on HSI or FLI calculation is cost-effective in primary care settings.…”
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Ecological Risk Assessment of Watersheds Based on Adaptive Cycling Theory—A Case Study of Poyang Lake Ecological and Economic Zone by Yixi Gu, Jiaxuan Wang, Xinyi Su, Kaili Zhang

“…Multi-scenario simulations using an Ordered Weighted Averaging (OWA) algorithm identified risk-uncertain zones in southeastern hilly areas and northern Poyang Lake waters, while distinguishing stable high/low-risk regions unaffected by decision-making influences. …”
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Key Technologies in Intelligent Seeding Machinery for Cereals: Recent Advances and Future Perspectives by Wei Liu, Jinhao Zhou, Tengfei Zhang, Pengcheng Zhang, Mengjiao Yao, Jinhong Li, Zitong Sun, Guoxin Ma, Xinxin Chen, Jianping Hu

“…In the future, more advanced multi-algorithm and multi-sensor fusion technologies for soil property detection, optimal seeding rate decisions, seeding rates, and seed position control are likely to evolve. …”
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MRI-based radiomic and machine learning for prediction of lymphovascular invasion status in breast cancer by Cici Zhang, Minzhi Zhong, Zhiping Liang, Jing Zhou, Kejian Wang, Jun Bu

“…Methods A total of 454 patients with BC with known LVI status who underwent breast MRI were enrolled and randomly assigned to the training and validation sets at a ratio of 7:3. Radiomic features were extracted from T2WI and dynamic contrast-enhanced (DCE) of MRI sequences, the optimal feature filter and LASSO algorithm were used to obtain the optimal features, and eight machine learning algorithms, including LASSO, logistic regression, random forest, k-nearest neighbor (KNN), support vector machine, gradient boosting decision tree, extreme gradient boosting, and light gradient boosting machine, were used to construct models for predicating LVI status in BC. …”
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