Identification of Candidate Tolerogenic CD8+ T Cell Epitopes for Therapy of Type 1 Diabetes in the NOD Mouse Model by Cailin Yu, Jeremy C. Burns, William H. Robinson, Paul J. Utz, Peggy P. Ho, Lawrence Steinman, Alan B. Frey

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Comprehensive improvement of energy efficiency and indoor environmental quality for university library atrium—A multi-objective fast optimization framework by Shen Xu, Yongzhong Chen, Jianlin Liu, Jian Kang, JinFeng Gao, Yuchen Qin, Wenjun Tan, Gaomei Li

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Nasopharyngeal Carcinoma Subtype Discovery via Immune Cell Scores from Tumor Microenvironment by Yanbo Sun, Yun Liu, Hanqi Chu

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Overcoming the challenges of data integration in ecosystem studies with machine learning workflows: an example from the Santos project by Gustavo Fonseca, Danilo Candido Vieira

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Overcoming the challenges of data integration in ecosystem studies with machine learning workflows: an example from the Santos project by Gustavo Fonseca, Danilo Candido Vieira

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Machine Learning Analysis to Identify Predictive Factors of Caudal Epidural Pulse Radiofrequency in the Treatment of Coccygodynia by Sir E, Aydogan S, Batur Sir GD, Celenlioglu AE

“…The findings generated by these algorithms are compared with respect to the accuracy of the results.Results: Symptom duration, angular deformation and NRS at admission are the most significant factors impacting therapy success in coccygodynia patients. …”
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High-accuracy prediction of vessels’ estimated time of arrival in seaports: A hybrid machine learning approach by Sunny Md. Saber, Kya Zaw Thowai, Muhammad Asifur Rahman, Md. Mehedi Hassan, A.B.M. Mainul Bari, Asif Raihan

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Statistical analysis of sizing features of dust generated under the mechanical metal-working by N. N. Azimova, E. N. Ladosha, S. N. Kholodova, D. S. Tsymbalov, O. V. Yatsenko

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Identification of a Hypoxia-Angiogenesis lncRNA Signature Participating in Immunosuppression in Gastric Cancer by Zicheng Wang, Xisong Liang, Hao Zhang, Zeyu Wang, Xun Zhang, Ziyu Dai, Zaoqu Liu, Jian Zhang, Peng Luo, Jiarong Li, Quan Cheng

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Personalizing mHealth Interventions for Occupational Stress: Protocol for a Randomized Pilot Study by Beatrix Kunas, Oliver Jung, Christoph Schranz, Mathias Schmoigl-Tonis, Manuela Ploessnig, Anton-Rupert Laireiter

“…The app offered interventions based on algorithms, which altered the probability of their selection after learning from the data, thereby personalizing the user experience. …”
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Analysis of Energy Consumption in a Federated Learning-Based Zero-Touch Network by Urooj Yousuf Khan, Musharaf Ali Talpur, Umme Laila, Samar Raza Talpur

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Identification of Disulfidptosis-Related Genes and Molecular Subgroups in Rheumatoid Arthritis for Diagnostic Model and Patient Stratification by Liu X, Wang S, Du X, Wang Y, Mo L, Li H, Qu Z, Wang X, Sun J, Li Y, Wang J

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Serum TGF-β1 and CD14 Predicts Response to Anti-TNF-α Therapy in IBD by Stepan Coufal, Miloslav Kverka, Jakub Kreisinger, Tomas Thon, Filip Rob, Martin Kolar, Zuzana Reiss, Dagmar Schierova, Klara Kostovcikova, Radka Roubalova, Lukas Bajer, Zuzana Jackova, Martin Mihula, Pavel Drastich, Jana Tresnak Hercogova, Michaela Novakova, Martin Vasatko, Milan Lukas, Helena Tlaskalova-Hogenova, Zuzana Jiraskova Zakostelska

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Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recog... by Andrea P Garzón-Partida, Kimberly Magaña-Plascencia, Diana Emilia Martínez-Fernández, Joaquín García-Estrada, Sonia Luquin, David Fernández-Quezada

“…The collected data will then be used to train models with a neural network, which will then be validated against other models and compared with other algorithms. Demographic, psychological, digital biomarkers, and craving profiles will be created, correlations will be analyzed, and they will be compared with controls to generate a digital phenotype of SUD. …”
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Distribution of age at natural menopause, age at menarche, menstrual cycle length, height and BMI in BRCA1 and BRCA2 pathogenic variant carriers and non-carriers: results from EMBR... by Nasim Mavaddat, Debra Frost, Emily Zhao, Daniel R. Barnes, Munaza Ahmed, Julian Barwell, Angela F. Brady, Paul Brennan, Hector Conti, Jackie Cook, Harriet Copeland, Rosemarie Davidson, Alan Donaldson, Emma Douglas, David Gallagher, Rachel Hart, Louise Izatt, Zoe Kemp, Fiona Lalloo, Zosia Miedzybrodzka, Patrick J. Morrison, Jennie E. Murray, Alex Murray, Hannah Musgrave, Claire Searle, Lucy Side, Katie Snape, Vishakha Tripathi, Lisa Walker, Stephanie Archer, D. Gareth Evans, Marc Tischkowitz, Antonis C. Antoniou, Douglas F. Easton

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Lightweight CNN model for automatic detection and depth estimation of subsurface voids using GPR B-scan data by Abdelaziz Mojahid, Driss EL Ouai, Khalid EL Amraoui, Khalil EL-Hami, Hamou Aitbenamer, Jochem Verrelst, Pier Matteo Barone

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Mapping forest types along ecological gradient in Pakistan by Naveed Ahmad, Syed Ghias Ali

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Investigating potential biomarkers associated with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis using Mendelian randomization and transcriptomic analysis by Yujia Wang, Zhimin Chen, Kaiqi Huang, Keng Ye, Shiwei He, Yanfang Xu, Hong Chen

“…Early identification and accurate diagnosis of AAV is crucial for improving prognosis. However, research on biomarkers associated with AAV is limited. …”
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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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Identification of Diagnostic Biomarkers and Therapeutic Targets in Sepsis-Associated ARDS via Combining Bioinformatics with Machine Learning Analysis by Liu T, Gao L, Li X

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