Optimized Allocation of Flood Control Emergency Materials Based on Loss Quantification by Wei Wang, Yunqing Wang, Li Huang, Yue Song

“…The center of gravity method is used to address demand when constructing the quantitative function of out‐of‐stock loss. The NSGA‐II algorithm was selected to generate the results after the method comparison to ultimately determine the Pareto solution of the model. …”
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Machine Learning and Deep Learning Techniques for Prediction and Diagnosis of Leptospirosis: Systematic Literature Review by Suhila Sawesi, Arya Jadhav, Bushra Rashrash

“…MethodsUsing Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS), and Prediction model Risk of Bias Assessment Tool (PROBAST) tools, we conducted a comprehensive review of studies applying ML and DL models for leptospirosis detection and prediction, examining algorithm performance, data sources, and validation approaches. …”
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Optimizing the dynamic treatment regime of outpatient rehabilitation in patients with knee osteoarthritis using reinforcement learning by Sijia Liu, Jiawei Luo, Chengqi He

“…Then, based on the key features screened out, a dynamic treatment recommendation system was constructed by using deep reinforcement learning algorithms, including Deep Deterministic Policy Gradien(DDPG), Deep Q-Network(DQN) and Batch-Constrained Q-learning(BCQ). …”
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Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis by Hamed Hajishah, Danial Kazemi, Ehsan Safaee, Mohammad Javad Amini, Maral Peisepar, Mohammad Mahdi Tanhapour, Arian Tavasol

“…In total, 346 machine learning models were evaluated, with the most common algorithms being random forest, logistic regression, and gradient boosting. …”
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Identification and Evaluation of Lipocalin-2 in Sepsis-Associated Encephalopathy via Machine Learning Approaches by Hu J, Chen Z, Wang J, Xu A, Sun J, Xiao W, Yang M

“…Subsequently, neuroinflammation-related genes were obtained to construct a neuroinflammation-related signature. The AddModuleScore algorithm was used to calculate neuroinflammation scores for each cell subpopulation, whereas the CellCall algorithm was used to assess the crosstalk between neutrophils and other cell subpopulations. …”
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Machine Learning and Interpretability Study for Predicting 30-Day Unplanned Readmission Risk of Schizophrenia: A Retrospective Study by Tan Y, Chen G, Wang S, Zhan X, Cheng R, Qiao L, Zhang Z, Liu Y

“…Models were constructed after screening variables using the multiple linear regression and feature importance methods. …”
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Enhanced thyroid nodule detection and diagnosis: a mobile-optimized DeepLabV3+ approach for clinical deployments by Changan Yang, Muhammad Awais Ashraf, Mudassar Riaz, Pascal Umwanzavugaye, Kavimbi Chipusu, Hongyuan Huang, Yueqin Xu

“…A high IoU value in medical imaging analysis reflects the model’s ability to accurately delineate object boundaries.ConclusionDeepLabV3+ represents a significant advancement in thyroid nodule segmentation, particularly for thyroid cancer screening and diagnosis. …”
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Prevention of Cardiometabolic Syndrome in Children and Adolescents Using Machine Learning and Noninvasive Factors: The CASPIAN-V Study by Hamid Reza Marateb, Mahsa Mansourian, Amirhossein Koochekian, Mehdi Shirzadi, Shadi Zamani, Marjan Mansourian, Miquel Angel Mañanas, Roya Kelishadi

“…We applied the XGBoost algorithm to analyze key noninvasive variables, including self-rated health, sunlight exposure, screen time, consanguinity, healthy and unhealthy dietary habits, discretionary salt and sugar consumption, birthweight, and birth order, father and mother education, oral hygiene behavior, and family history of dyslipidemia, obesity, hypertension, and diabetes using five-fold cross-validation. …”
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Health-Related Quality-of-Life Utility Values in Adults With Late-Onset Pompe Disease: Analyses of EQ-5D Data From the PROPEL Clinical Trial by Alison Griffiths, Simon Shohet, Neil Johnson, Alasdair MacCulloch

“…In PROPEL, EQ-5D-5L values were assessed at screening and at weeks 12, 26, 38, and 52. EQ-5D-5L utility values were mapped to EQ-5D-3L values using the van Hout algorithm as recommended by the EuroQoL and the National Institute of Health and Care Excellence position statement at time of analysis. …”
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Retinal Microvascular Characteristics—Novel Risk Stratification in Cardiovascular Diseases by Alexandra Cristina Rusu, Klara Brînzaniuc, Grigore Tinica, Clément Germanese, Simona Irina Damian, Sofia Mihaela David, Raluca Ozana Chistol

“…This study aims to identify the retinal microvascular features associated with CHDs and evaluate their potential use in a CHD screening algorithm in conjunction with traditional risk factors. …”
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Sialyltransferase-related genes as predictive factors for therapeutic response and prognosis in cervical cancer by Jia Shao, Can Zhang, Yaonan Tang, Aiqin He, Xiangyan Cheng

“…Cox regression analysis and “glmnet” R package were applied to establish the relevant risk model. “MCPcounter” R package, ESTIMATE algorithm and TIMER online tools were used to depict the tumor immune microenvironment in CC. …”
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A hybrid super learner ensemble for phishing detection on mobile devices by Routhu Srinivasa Rao, Cheemaladinne Kondaiah, Alwyn Roshan Pais, Bumshik Lee

“…Furthermore, many of these techniques are unsuitable for mobile devices, which face additional constraints, such as limited RAM, smaller screen sizes, and lower computational power. To address these limitations, this paper proposes a novel hybrid super learner ensemble model named Phish-Jam, a mobile application specifically designed for phishing detection on mobile devices. …”
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Prediction of mortality risk in patients with severe community-acquired pneumonia in the intensive care unit using machine learning by Jingjing Pan, Tao Guo, Haobo Kong, Wei Bu, Min Shao, Zhi Geng

“…Five machine learning algorithms were used to build predictive models. Models were evaluated through nested cross-validation to select the best one. …”
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Prospective Validation and Usability Evaluation of a Mobile Diagnostic App for Obstructive Sleep Apnea by Pedro Amorim, Daniela Ferreira-Santos, Marta Drummond, Pedro Pereira Rodrigues

“…Current guidelines recommend the development of clinical prediction algorithms in screening prior to PSG. A recent intuitive and user-friendly tool (OSABayes), based on a Bayesian network model using six clinical variables, has been proposed to quantify the probability of OSA. …”
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Identification of retinol dehydrogenase 10 as a shared biomarker for metabolic dysfunction-associated steatotic liver disease and type 2 diabetes mellitus by Fangyu Li, Rui Li, Hongjun Deng

“…The LASSO algorithm and ROC curve identified Retinol Dehydrogenase 10 (RDH10) as the best diagnostic gene for MASLD and T2DM. …”
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STOP-BANG: a Mandatory Tool for Targeted Respiratory Therapy in Bariatric Patients by R. D. Skvortsova, K. А. Аnisimova, K. А. Popova, V. А. Pavlova, А. N. Kulikov, D. I. Vasilevsky, S. G. Balandov, Z. А. Zaripova, А. А. Kazachenko, Yu. D. Rabik, T. S. Razumovskaya

“…Identification of patients with obstructive sleep apnea syndrome and high respiratory risk, optimization of the screening algorithm for these patients and administration of preventive non-invasive lung ventilation, makes it possible to prevent the development of perioperative complications, reduce duration of hospital stay and reduce mortality in patients undergoing surgery and bariatric surgery specifically.The objective: to evaluate the effectiveness of STOP-BANG questionnaire for preventive targeted respiratory therapy to reduce the risk of complications in bariatric patients. …”
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Weak fault diagnosis method for rolling bearings under strong background noise based on EEMD-FK-AMCKD by XIE Guizhong, XU Shuaiqiang, DU Wenliao, LUO Shuangqiang, LI Hao, WANG Liangwen, GONG Xiaoyun

“…ObjectiveTo address the challenge of accurately capturing weak features in vibration signals under strong noise interference, a joint filtering method combining ensemble empirical mode decomposition (EEMD), fast kurtogram (FK), and adaptive maximum correlation kurtosis deconvolution (AMCKD) was proposed.MethodsFirstly, the vibration signal was decomposed into multiple intrinsic mode functions (IMF) via EEMD for multiscale analysis. …”
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Construction of mitochondrial signature (MS) for the prognosis of ovarian cancer by Miao Ao, You Wu, Kunyu Wang, Haixia Luo, Wei Mao, Anqi Zhao, Xiaomeng Su, Yan Song, Bin Li

“…After univariate Cox analysis, prognostic genes were carried out for modeling mitochondria signature (MS) based on 101 combinations of 10 machine learning algorithms. …”
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A comparative study of bone density in elderly people measured with AI and QCT by Min Guo, Min Guo, Yu Zhang, Yu Zhang, XinXin Gu, XinXin Gu, Xuhui Liu, Xuhui Liu, Fei Peng, Fei Peng, Zongjun Zhang, Zongjun Zhang, Mei Jing, Mei Jing, Yingxia Fu, Yingxia Fu

“…Early detection of reduced bone mineral density (BMD) through opportunistic screening is critical for preventing fragility fractures. …”
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Joint analysis of single-cell RNA sequencing and bulk transcriptome reveals the heterogeneity of the urea cycle of astrocytes in glioblastoma by Minfeng Tong, Qi Tu, Lude Wang, Huahui Chen, Xing Wan, Zhijian Xu

“…For bulk RNA-seq, univariate Cox and LASSO analyses were undertaken to screen prognostic genes, while multivariate Cox regression analysis was applied to set up a prognostic model. …”
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