Analysis of the molecular subtypes and prognostic models of anoikis-related genes in colorectal cancer by Lei Shen, Kang Hou, Jifeng Zhang, Xiaodong Li

“…Additionally, various computational algorithms were employed to evaluate the immunotherapeutic responses of different risk groups. …”
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Features of tactics of inspection of accident sites in the investigation of illegal interference in the activities of energy facilities using unmanned vehicles by S. L. Kislenko, A. B. Smushkin

“…At the same time, the importance of urgently studying the volatile memory of a working device is stated.Conclusions about the achievement of the research goal: the paper proposes adaptive algorithms for the investigator's actions in various investigative situations: when the functioning of the device was suppressed by electronic warfare; when the UAV was physically damaged or destroyed; when an attacker with a UAV control device (remote control, smartphone, laptop, special glasses, etc.) was detained at the scene; when the control device is detected, but the attacker himself has disappeared; when the attacker has destroyed the control device; when information from the UAV (video and sensor readings) was transmitted not only to the operator's device, but also to another addressee; when the operator was detained on the territory of the fuel and energy complex. …”
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3D anatomical digital twins: New generation virtual models to navigate robotic partial nephrectomy by Daniele Amparore, Alberto Piana, Federico Piramide, Sabrina De Cillis, Enrico Checcucci, Cristian Fiori, Francesco Porpiglia

“…Textures are created from intraoperative robotic surgery images using machine learning algorithms. The result is a 3D model ‐ digital twin that replicates the organ's shape and appearance. …”
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Sex differences in alcohol use patterns and related harms: A mixed-methods, cross-sectional study of men and women in northern Tanzania. by Madeline McNee, Niveditha Badrinarayanan, Eleanor Strand, Thiago Augusto Hernandes Rocha, Timothy Antipas Peter, Yvonne Sawe, Anna Tupetz, Diego Galdino França, Judith Boshe, Joao Ricardo Nickenig Vissoci, Monica H Swahn, Blandina Mmbaga, Catherine Staton

“…Differences in scores by sex were assessed using unpaired t-tests. K-means algorithms were run independently in both samples. Deductive thematic analysis was conducted on FGDs with community members, injury patients, and injury patient relatives. …”
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A Comprehensive Review of Optimizing Multi-Energy Multi-Objective Distribution Systems with Electric Vehicle Charging Stations by Mahesh Kumar, Aneel Kumar, Amir Mahmood Soomro, Mazhar Baloch, Sohaib Tahir Chaudhary, Muzamil Ahmed Shaikh

“…Therefore, at the conclusion of this review, the optimization of electric vehicle charging stations and distributed generation presents both the practical and theoretical importance of implementing metaheuristic algorithms in real-world scenarios. In the same way, their practical integration will provide the transportation system with a robust and sustainable solution.…”
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Machine Learning-Based Prediction of Postoperative Deep Vein Thrombosis Following Tibial Fracture Surgery by Humam Baki, İsmail Bülent Özçelik

“…A total of 42 predictive models were developed using combinations of six ML algorithms—logistic regression, support vector machine, random forest, extreme gradient boosting, Light Gradient Boosting Machine (LightGBM), and neural networks—and seven feature selection methods, including SHapley Additive exPlanations (SHAP), Least Absolute Shrinkage and Selection Operator (LASSO), Boruta, recursive feature elimination, univariate filtering, and full-variable inclusion. …”
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Application of statistical methods for predicting udp-flood attacks by M. V. Tumbinskaya, V. V. Volkov, B. G. Zagidullin

“…In order to improve the level of protection against DDoS attacks, further research should be aimed at developing methods for combating UDP-flood attacks and algorithms increasing the information security of web resources, as well as implementing measures to improve the security of web-based resources.…”
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Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…Basophil count, while ranked highest by SHAP, showed low sensitivity, highlighting the difference between algorithmic weight and bedside utility. Conclusion: These findings support the integration of routine, readily available laboratory data into an explainable AI framework to accurately predict culture positivity. …”
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Diagnosis and Classification of Two Common Potato Leaf Diseases (Early Blight and Late Blight) Using Image Processing and Machine Learning by H. Koroshi Talab, D. Mohammad Zamani, M. Gholami Parashkoohi

“…This study presents a framework for diagnosing early blight and late blight diseases in potatoes using a combination of Relief feature selection algorithms and Random Forest classification, along with color, texture, and shape features in three color spaces: RGB, HSV, and CIELAB (Lab*). …”
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Detection of Mycotoxin Contamination in Foods Using Artificial Intelligence: A Review by Ashish Aggarwal, Akanksha Mishra, Nazia Tabassum, Young-Mog Kim, Fazlurrahman Khan

“…Deep learning models, machine learning algorithms, and neural networks were implemented to analyze elaborate datasets from different analytical platforms. …”
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Identification of glucocorticoid-related genes in systemic lupus erythematosus using bioinformatics analysis and machine learning. by Yinghao Ren, Weiqiang Chen, Yuhao Lin, Zeyu Wang, Weiliang Wang

“…Furthermore, we utilized least absolute shrinkage and selection operator (LASSO) regression and Random Forest (RF) algorithms to screen for hub genes. We then validated the expression of these hub genes and constructed nomograms for further validation. …”
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A Robust Regression-Based Modeling to Predict Antiplasmodial Activity of Thiazolyl–Pyrimidine Hybrid Derivatives against <i>Plasmodium falciparum</i> by Kevin S. Umoette, Charles O. Nnadi, Wilfred O. Obonga

“…Regression models were built using scikit-learn algorithms: multiple linear regression (MLR), k-Nearest Neighbors (kNN), Support Vector Regressor (SVR), and Random Forest Regressor (RFR) to predict the pIC₅₀ of the test set. …”
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FQDNet: A Fusion-Enhanced Quad-Head Network for RGB-Infrared Object Detection by Fangzhou Meng, Aoping Hong, Hongying Tang, Guanjun Tong

“…Compared to state-of-the-art RGB-IR object detection algorithms, our method strikes a better balance between detection accuracy and computational efficiency while exhibiting strong robustness across diverse detection scenarios.…”
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Principles of physical factor selection in the early postoperative period of breast cancer treatment: a randomized controlled study by Inna S. Evstigneeva

“…Current models of onco-rehabilitation do not consider the patient’s functional impairment during combined treatment until the patient becomes incapacitated and the impairment develops into a chronic condition. AIM. To develop algorithms for selecting physical factors depending on the clinical and functional state of patients after radical surgical treatment of breast cancer (BC) in the early postoperative period. …”
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Quantum-Inspired Control Strategies for Reducing DC-Link Voltage Fluctuations in DFIG Wind Energy Converters by Sarika Shrivastava, Saifullah Khalid, Dinesh Kumar Nishad

“…By incorporating quantum-inspired algorithms into the Grid-Side Converter (GSC) control framework, the strategy dynamically adjusts PI gains using qubit-based probabilistic modeling&#x2014;where control parameters exist simultaneously in multiple potential states, similar to quantum bits existing in both 0 and 1 states concurrently. …”
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Association between resolved hepatitis B virus infection and depression in American adults : a cross-sectional study by Zihan Qin, Yizhuo Liu, Yifei Liu, Anqi Yang, Ruoyi Zhang, Kun Zhang, Shutian Zhang

“…Propensity score matching (PSM) was performed to balance baseline characteristics. Algorithms such as inverse probability of treatment weighting (IPTW) were also applied. …”
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Extracting Information from Unstructured Medical Reports Written in Minority Languages: A Case Study of Finnish by Elisa Myllylä, Pekka Siirtola, Antti Isosalo, Jarmo Reponen, Satu Tamminen, Outi Laatikainen

“…The results of this research show that relevant information can be effectively extracted from Finnish medical reports using classification algorithms with default parameter values. For the detection of breast tumour mentions from medical texts, classifiers achieved high accuracy, almost 90%. …”
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Novel estrogen-related gene variants identified by whole-exome sequencing in pregnancy-associated intrahepatic cholestasis by Hua Lai, Siming Xin, Jinliang Zhang, Yang Hu, Wenjuan Fan, Hong Wan, Bowen Chen, Yang Zou, Xiaoming Zeng, Xianxian Liu

“…These variants exhibited the following characteristics: (1) complete absence in 1,237 controls and all public genomic databases (1000 Genomes, ExAC, and dbSNP); (2) evolutionary conservation of the affected residues, with unanimous pathogenic predictions from all algorithms (PolyPhen-2: damaging; SIFT: deleterious; MutationTaster: disease-causing); (3) molecular modeling demonstrating structural perturbations in critical functional domains, including steroid-binding and redox partner interaction sites. …”
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Federated Learning Based on an Internet of Medical Things Framework for a Secure Brain Tumor Diagnostic System: A Capsule Networks Application by Roman Rodriguez-Aguilar, Jose-Antonio Marmolejo-Saucedo, Utku Köse

“…It enables machine learning or deep learning algorithms to establish a client–server relationship, whereby specific parameters are securely shared between models while maintaining the integrity of the learning tasks being executed. …”
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Improved breast cancer risk prediction using chromosomal-scale length variation by Yasaman Fatapour, James P. Brody

“…We used machine learning algorithms to find a model that best differentiates the women with breast cancer from the women without breast cancer based on the set of 88 numbers that characterize each woman’s germline genome. …”
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