GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data by Muhammad Iqbal, Arshad Iqbal, Humaira Ayub, Maqbool Khan, Naveed Ahmad, Yasir Javed, Mohammed Ali Alshara

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Treatment of Chronic Endometritis with Vague Symptoms in Patients with Endometrial Hyperplasia by N. I. Volotskaya, E. P. Golubinskaya, E. Yu. Zyablitskaya, Р. E. Maksimova

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FLIGHT EXPERT RISK ASSESSMENT OF AIRCRAFT GROUP AT THEIR PROXIMITY USING A PROGRAM-MANAGER by D. A. Mikhaylin

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Principal Component Analysis and Bacterial Foraging Optimization for Credit Scoring by Jennifer Arjun, Marsudi Wahyu Kisworo, Edi Surya Negara, Usman Ependi

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Identification model of mine water inrush source based on XGBoost and SHAP by Bencong Kou, Tingxin Wen

“…The model uses Ca2+, Mg2+, K+ + Na+, HCO3 -, Cl-, SO4 2-, Hardness, and pH as discriminators, and the key parameters in the XGBoost model are optimized by introducing the improved sparrow search algorithm. …”
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Identification of a novel immunogenic cell death-related classifier to predict prognosis and optimize precision treatment in hepatocellular carcinoma by Dongjing Zhang, Bingyun Lu, Qianqian Ma, Wen Xu, Qi Zhang, Zhiqi Xiao, Yuanheng Li, Ren Chen, An-jiang Wang

“…In this study, we systematically analyzed the mRNA profiles of ICD-related genes in 1847 HCC patients and identified three molecular subtypes with significantly different immune features and prognostic stratification. …”
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Artificial Intelligence for Unstructured Data Processing by Yohanes Bowo Widodo, Febrianti Widyahastuti, Mohammad Narji, Sondang Sibuea

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Understanding students’ sentiment from feedback with a new feature selection and semantics networks by Tran Anh Tuan, Dao Thi Thanh Loan, Nichnan Kittiphattanabawon

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Wearable devices for patient monitoring in the intensive care unit by Alessandra Angelucci, Massimiliano Greco, Maurizio Cecconi, Andrea Aliverti

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Developing a Predictive Model for Stroke Disease Detection Using a Scalable Machine Learning Approach by Assefa Senbato Genale, Tsion Ayalew Dessalegn

“…We have implemented four scalable algorithms: logistic regression, random forest, gradient-boosting tree, and decision tree, using a dataset that was collected from a Medical Quality Improvement Consortium database. …”
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Machine learning-based real-time prediction of duodenal stump leakage from gastrectomy in gastric cancer patients by Jae Hun Chung, Jae Hun Chung, Jae Hun Chung, Yushin Kim, Dongjun Lee, Dongwon Lim, Dongwon Lim, Dongwon Lim, Sun-Hwi Hwang, Sun-Hwi Hwang, Sun-Hwi Hwang, Si-Hak Lee, Si-Hak Lee, Si-Hak Lee, Woohwan Jung

“…The confidence scores of the model indicated that the DSL predictions became more reliable over time.ConclusionThe study concluded that ML models, notably the XGB algorithm, can effectively predict DSL in real-time using comprehensive clinical data, enhancing the clinical decision-making process for GC patients.…”
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Nomogram model using serum Club cell secretory protein 16 to predict prognosis and acute exacerbation in patients with idiopathic pulmonary fibrosis by Yaqiong Tian, Xuan Zhou, Mi Tian, Lijun Ren, Ruyi Zou, Hanyi Jiang, Miaomiao Xie, Mei Huang, Jingjing Ding, Yin Liu, Jingyu Chen, Min Cao, Hourong Cai

“…COX regression and LASSO algorithm were used to screen featured characteristics. …”
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Land Cover Transformations in Mining-Influenced Areas Using PlanetScope Imagery, Spectral Indices, and Machine Learning: A Case Study in the Hinterlands de Pernambuco, Brazil by Admilson da Penha Pacheco, João Alexandre Silva do Nascimento, Antonio Miguel Ruiz-Armenteros, Ubiratan Joaquim da Silva Junior, Juarez Antonio da Silva Junior, Leidjane Maria Maciel de Oliveira, Sylvana Melo dos Santos, Fernando Dacal Reis Filho, Carlos Alberto Pessoa Mello Galdino

“…The methodology consisted of monitoring and evaluating environmental impacts using the k-Nearest Neighbors (kNN) algorithm, spectral indices (Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI)), and hydrological data, covering the period from 2018 to 2023. …”
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Optimal off-grid electricity supply for a residential complex using water-energy-economic-environmental nexus by Mozhgan Jafari, Hoseyn Sayyaadi

“…A multi-objective optimization framework was applied, using Genetic Algorithms alongside TOPSIS and AHP decision-making methods, considering the Water-Energy-Economic-Environmental (WEEE) Nexus. …”
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Integration of Bulk and Single-Cell Transcriptomics Reveals BCL2L14 as a Novel IGKC+ T Cell-Associated Therapeutic Target in Breast Cancer by He J, Akhtar A, Li J, Wei Q, Yuan Y, Ran J, Ma Y, Chen D

“…To pinpoint key regulatory genes, we applied machine learning algorithms. Based on the hub genes identified, we constructed a prognostic risk model and developed a nomogram to aid clinical decision-making. …”
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Optimizing Cardiovascular Risk Assessment with a Soft Voting Classifier Ensemble by Ammar Oad, Zulfikar Ahmed Maher, Imtiaz Hussain Koondhar, Karishima Kumari, Hammad Bacha

“…The proposed ensemble soft voting classifier employs an ensemble of seven machine learning algorithms to provide binary classification, the Naïve Bayes K Nearest Neighbor SVM Kernel Decision Tree Random Forest Logistic Regression and Support Vector Classifier. …”
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Numerical-analytical modeling of oil extraction from oil fields with a gas cap using horizontal wells with automatic history matching by D. V. Shevchenko, A. A. Salamatin, A. D. Yarullin, S. A. Usmanov, V. V. Saveliev, V. A. Sudakov, A. P. Roschektaev, E. V. Yudin, D. S. Vorobyov, V. V. Sorokina, A. A. Sveshnikova

“…The numerical scheme of the model was implemented as a computational library in the Python 3.6 programming language.The algorithm was tested on oil deposits with a gas cap in the South Yamal oil and gas region and showed good results in history matching and forecasting calculations. …”
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Optimized Ensemble Methods for Classifying Imbalanced Water Quality Index Data by Zaharaddeen Karami Lawal, Ali Aldrees, Hayati Yassin, Salisu Dan'azumi, Sujay Raghavendra Naganna, Sani I. Abba, Saad Sh. Sammen

“…The dataset of this study comprises 301 records collected from eight monitoring stations along the Kinta River, encompassing 31 pollution indicators, including hydrological, chemical, physical, and microbiological parameters. Six algorithms used include decision tree, logistic regression, random forest, support vector machine, AdaBoost, and XGBoost. …”
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Comparing the Effect of Beractant (Beraksurf™) with That of Poractant Alfa (Curosurf®) on the Need for Intermittent Positive Pressure Ventilation in Neonatal Respiratory Distress S... by Yosra Khazani, Sirous Fathi Manesh, Elnaz Shaseb, Parvin Sarbakhsh

“…Results The proportions of the required IPPV outcome were 29.3% and 59.4% in the BeraksurfTM group and Curosurf®, respectively. …”
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Machine Learning in Maritime Safety for Autonomous Shipping: A Bibliometric Review and Future Trends by Jie Xue, Peijie Yang, Qianbing Li, Yuanming Song, P. H. A. J. M. van Gelder, Eleonora Papadimitriou, Hao Hu

“…Future research will concentrate on three main areas: evolving safety objectives towards proactive management and autonomous coordination, developing advanced safety technologies, such as bio-inspired sensors, quantum machine learning, and self-healing systems, and enhancing decision-making with machine learning algorithms such as generative adversarial networks (GANs), hierarchical reinforcement learning (HRL), and federated learning. …”
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