Ethical Challenges of Using the Internet of Behavior in the Medical and Healthcare Practice by Zahra Sadeqi-Arani, Esmaeil Mazroui Nasrabadi

“…Additionally, reliance on algorithms for IoB data analysis should not diminish human oversight in healthcare decision-making. …”
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Diagnosis of Coronary Heart Diseases Using Gene Expression Profiling; Stable Coronary Artery Disease, Cardiac Ischemia with and without Myocardial Necrosis. by Nabila Kazmi, Tom R Gaunt

“…With the recent advances in genomic tools and technologies there is potential to predict and diagnose heart disease using molecular data from analysis of blood cells. …”
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Intelligent Processing Methods by Veronika V. Tolmanova, Denis A. Andrikov

“…These methods, together with modern algorithms and computer models, allow extracting valuable information from huge volumes of raw data, as well as analyzing and forecasting various phenomena and trends. …”
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Forest Fire Hazard Assessment using Remote Sensing Data and Machine Learning, Case Study of Jijel, Algeria by Matougui Zakaria, Zouidi Mohamed

“…This paper assesses wildfire hazards in Jijel, Algeria, using advanced machine learning techniques combined with spatial analysis of environmental and anthropogenic factors. Two algorithms, K-Nearest Neighbours (KNN) and Histogram-Based Gradient Boosting (HGB), were employed. …”
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Resonant solitary states in complex networks by Jakob Niehues, Serhiy Yanchuk, Rico Berner, Jürgen Kurths, Frank Hellmann, Mehrnaz Anvari

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A Human-Centric, Uncertainty-Aware Event-Fused AI Network for Robust Face Recognition in Adverse Conditions by Akmalbek Abdusalomov, Sabina Umirzakova, Elbek Boymatov, Dilnoza Zaripova, Shukhrat Kamalov, Zavqiddin Temirov, Wonjun Jeong, Hyoungsun Choi, Taeg Keun Whangbo

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Integrated bioinformatics identifies ferroptosis biomarkers and therapeutic targets in idiopathic pulmonary arterial hypertension by Yuhao Zhang, Tao Qian, Wei Jiang, Haoyong Yuan, Ting Lu, Ni Yin, Zhongshi Wu, Can Huang

“…GO and KEGG analyses were performed to explore biological functions and potential pathways. LASSO and SVM-RFE algorithms were used to identify optimal gene biomarkers for IPAH. …”
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%diag_test: a generic SAS macro for evaluating diagnostic accuracy measures for multiple diagnostic tests by Jacques K. Muthusi, Peter W. Young, Frankline O. Mboya, Samuel M. Mwalili

“…We also used the macro to reproduce results of published work on evaluating performance of multiple classification machine learning algorithms for predicting coronary artery disease. Conclusion The SAS macro presented here is a powerful analytic tool for analyzing data from multiple diagnostic tests. …”
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Marine soundscape forecasting: A deep learning-based approach by Shashidhar Siddagangaiah

“…Despite the rapid development of anomaly detection algorithms and deep-learning models for forecasting, their application to marine soundscapes remains unexplored. …”
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Analysis and Validation of Autophagy-Related Gene Biomarkers and Immune Cell Infiltration Characteristic in Bronchopulmonary Dysplasia by Integrating Bioinformatics and Machine Lea... by Xiao S, Ding Y, Du C, Lv Y, Yang S, Zheng Q, Wang Z, Zheng Q, Huang M, Xiao Q, Ren Z, Bi G, Yang J

“…Subsequently, the hub genes were identified by Lasso and Cytoscape with three machine-learning algorithms (MCC, Degree and MCODE). In addition, hub genes were validated with ROC, single-cell sequence and IHC in hyperoxia mice. …”
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Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients by Ran Du, Lijun Jing, Denggang Fu

“…The signature showed strong predictive power with AUC values of 0.68, 0.73, and 0.76 for 2-, 3-, and 5-year survival, respectively. …”
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SECONDGRAM: Self-conditioned diffusion with gradient manipulation for longitudinal MRI imputation by Brandon Theodorou, Anant Dadu, Mike Nalls, Faraz Faghri, Jimeng Sun

“…These models are computer algorithms that simulate how information changes. SECONDGRAM addresses data scarcity by generating realistic follow-up MRI imaging features, thereby enriching limited datasets. …”
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Estimating Winter Canola Aboveground Biomass from Hyperspectral Images Using Narrowband Spectra-Texture Features and Machine Learning by Xia Liu, Ruiqi Du, Youzhen Xiang, Junying Chen, Fucang Zhang, Hongzhao Shi, Zijun Tang, Xin Wang

“…Subsequently, machine learning algorithms were applied to develop estimation models for winter canola biomass. …”
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Factors influencing the response to periodontal therapy in patients with diabetes: post hoc analysis of a randomized clinical trial using machine learning by Nidia CASTRO DOS SANTOS, Arthur MANGUSSI, Tiago RIBEIRO, Rafael Nascimento de Brito SILVA, Mauro Pedrine SANTAMARIA, Magda FERES, Thomas VAN DYKE, Ana Carolina LORENA

“…We tested seven different algorithms: K-Nearest Neighbors, Decision Tree, Support Vector Machine, Random Forest, Extreme Gradient Boosting, and Logistic Regression. …”
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Quality monitoring of hybrid welding processes: A comprehensive review by Solomon Habtamu Tessema, Dariusz Bismor

“…Furthermore, the review highlights the integration of sensor data with AI/ML algorithms and digital twin technologies, enhancing the capabilities of quality monitoring systems. …”
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microRNA-497-5p-based screening identifies a novel synthetic lethal-type interaction via PKMYT1 and WEE1 in pleural mesothelioma by Nathanael Pruett, Sierra Wilferd, Anand Singh, Agnes Y. Choi, Shivani Dixit, Vivek Singh, Charlize Nguyen, Olivia Lin, David S. Schrump, Christopher L. Plaisier, Chuong D. Hoang

“…Surprisingly, multiple identified targets were not predicted by in silico algorithms. Using patient samples, cell lines, murine xenograft models, and our localized nanoparticle miRNA delivery platform, we validated miR-497-5p anti-tumor mechanisms, which consisted of pro-apoptotic and anti-cell-cycle effects. …”
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Development of a circadian-related prognostic signature highlights RBM17 as a stemness regulator in liver cancer by Jingsong Yan, Xiao Yang, Jiabin Lu, Shasha Wu, Yanchen Wang, Yuyang Du, Jingyi Zheng, Fenfen Wang, Han Gao, Hui Yang, Shaoyan Xi, Yan Li

“…Employing machine learning algorithms, we pinpointed four pivotal dysregulated LCGs. …”
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Visualising fibre path and generating G-code for melt electrowriting of tubular scaffolds using Grasshopper software by Kelly L. O’Neill, Taite McLoughlin, Georgia Van der Linden, Ignacio Lopez Buson, Naomi C. Paxton, Mary Polites, Paul D. Dalton

“…This visual prototyping platform through Rhinoceros and Grasshopper offers a new method in predicting fibre paths and incorporating scaffold design parameters, meeting the need for diverse tubular scaffolds in different fields. …”
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Modeling Asteroseismic Yields for the Roman Galactic Bulge Time-domain Survey by Trevor J. Weiss, Noah J. Downing, Marc H. Pinsonneault, Joel C. Zinn, Dennis Stello, Timothy R. Bedding, Kaili Cao, Marc Hon, Claudia Reyes, B. Scott Gaudi, Robert F. Wilson, Daniel Huber, Sanjib Sharma

“…The expected yield and stellar parameter precision we predict for Roman asteroseismology promise to characterize planet-hosting stellar populations and to resolve questions regarding the formation history of the bulge.…”
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Enhanced Detection of Intrusion Detection System in Cloud Networks Using Time-Aware and Deep Learning Techniques by Nima Terawi, Huthaifa I. Ashqar, Omar Darwish, Anas Alsobeh, Plamen Zahariev, Yahya Tashtoush

“…We generate real DoS traffic, including normal, Internet Control Message Protocol (ICMP), Smurf attack, and Transmission Control Protocol (TCP) classes, and develop nine predictive algorithms, combining traditional machine learning and advanced deep learning techniques with optimization methods, including the synthetic minority sampling technique (SMOTE) and grid search (GS). …”
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