Constructing a Glioblastoma Prognostic Model Related to Fatty Acid Metabolism Using Machine Learning and Identifying F13A1 as a Potential Target by Yushu Liu, Hui Deng, Ping Song, Mengxian Zhang

“…<b>Results:</b> C2, with the worst prognosis, may be associated with an immunosuppressive phenotype, which may be related to positive regulation of cell adhesion and lymphocyte-mediated immunity. …”
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Identification of anoikis-related genes in heart failure: bioinformatics and experimental validation by Lina Zhang, Jianjun Gu, Yan Jiang, Juan Xue, Ye Zhu

“…Conclusions These findings suggest that Tln1 and TGFβ2 may play important roles in HF development through the regulation of anoikis and may serve as therapeutic targets for HF. …”
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Reputational ranking of platform workers: on the gender discriminatory implications of users’ feedback by Elisa Parodi

“…The article questions whether this practice may constitute discrimination under the European Union equality law. …”
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Reframing the filter bubble through diverse scale effects in online music consumption by Dougal Shakespeare, Victor Chareyron, Camille Roth

“…Nevertheless, as the contribution of this work clearly shows, contradictory findings that algorithmic devices may both foster “bubbly” confinement dynamics and diverse exploration appear to stem, at least in part, from tensions surrounding information representation and scale. …”
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PLOD3 as a novel oncogene in prognostic and immune infiltration risk model based on multi-machine learning in cervical cancer by Lingling Qiu, Xiuchai Qiu, Xiaoyi Yang

“…These findings imply that this model may be applied to assess prognostic risk and identify potential therapeutic targets for CC patients.…”
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A graphical modelling approach to the dissection of highly correlated transcription factor binding site profiles. by Robert Stojnic, Audrey Qiuyan Fu, Boris Adryan

“…Clustered occurrence of multiple TFs at genomic sites may arise from chromatin accessibility and local cooperation between TFs, or binding sites may simply appear clustered if the profiles are generated from diverse cell populations. …”
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Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning by Bin He, Yan Cheng, Juan Wang, Ya Zhan, YanQun Liu

“…Trajectory analysis suggested that EF cells in AF may differentiate into both APF and SMC subtypes. …”
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Uncovering ethical biases in publicly available fetal ultrasound datasets by Maria Chiara Fiorentino, Sara Moccia, Mariachiara Di Cosmo, Emanuele Frontoni, Benedetta Giovanola, Simona Tiribelli

“…We argue that these biases may significantly influence DL model performance, which may lead to inequities in healthcare outcomes. …”
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Data Mining Classification Techniques for Diabetes Prediction by Hindreen Rashid Abdulqadir, Adnan Mohsin Abdulazeez, Dilovan Assad Zebari

“…Diabetes may be predicted and prevented by exploring critical diabetes characteristics by computational data extraction methods. …”
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Студент плюс-минус Интернет, или интернет-составляющая в компетенции русиста by Larisa Mikheeva

“…To accommodate these recent changes in cognitive mechanisms, the educational material, and the theoretical elements which are offered to the modern pupils and students, one should intensively focus on contextualizing fragmentary information, providing records in the modernized forms such as modules, flowcharts, algorithms, and mind maps. This approach may help students overcome the inconsistency in the reception and reproduction of the information and avoid serious mistakes in their comprehension of the presented facts. …”
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Data-Driven Healthcare: Critically Examining the Role of Self-care and Data-Driven Decision-Making in Diabetes Management by Anna Sigridur Islind, Helena Vallo Hult

“…The new self-care practices may be beneficial in many ways but can also potentially pose risks, and there is a corresponding need to understand underlying algorithms and biases that may affect users. …”
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The Influence of Network Structural Preference on Link Prediction by Yongcheng Wang, Yu Wang, Xinye Lin, Wei Wang

“…However, in the social network, link prediction may raise concerns about privacy and security, because, through link prediction algorithms, criminals can predict the friends of an account user and may even further discover private information such as the address and bank accounts. …”
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Load Balancing and Server Consolidation in Cloud Computing Environments: A Meta-Study by Mohammed Ala'anzy, Mohamed Othman

“…Just considering energy-efficiency (that can be attained efficiently by consolidate the servers) may not be enough for real applications because it may cause problems such as unbalanced load for each Physical Machine (PM). …”
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Active Learning for Medical Article Classification with Bag of Words and Bag of Concepts Embeddings by Radosław Pytlak, Paweł Cichosz, Bartłomiej Fajdek, Bogdan Jastrzębski

“…The proper choice of text representation for such algorithms may have a significant impact on their predictive performance. …”
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Combined use of respiratory multiplex PCR and procalcitonin to reduce antibiotic exposure in sickle-cell adult patients with acute chest syndrome (The ANTIBIO-STA study): a randomi... by Alexandre Sabaté-Elabbadi, Armand Mekontso-Dessap, François Lionnet, Aline Santin, Charlotte Verdet, Paul-Louis Woerther, Julien Lopinto, Matthieu Turpin, Alexandra Rousseau, Romane Lacoste-Badie, Keyvan Razazi, Guillaume Voiriot, Muriel Fartoukh

“…Summary: Background: Respiratory infection may account for 30% of acute chest syndrome (ACS) aetiologies. …”
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ZEB1 transcription factor promotes immune escape in melanoma by Christophe Caux, Stephane Dalle, Arnaud de la Fouchardière, Laurie Tonon, Maud Plaschka, Valentin Benboubker, Maxime Grimont, Justine Berthet, Jonathan Lopez, Myrtille Le-Bouar, Brigitte Balme, Garance Tondeur, Lionel Larue, Alain Puisieux, Yenkel Grinberg-Bleyer, Nathalie Bendriss-Vermare, Bertrand Dubois, Julie Caramel

“…Algorithm-based spatial reconstitution of tumors allowed the quantification of CD8+, CD4+ T cells number and their activation state (PD-1, Ki67). …”
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Privacy-Preserving Machine Learning (PPML) Inference for Clinically Actionable Models by Baris Balaban, Seyma Selcan Magara, Caglar Yilgor, Altug Yucekul, Ibrahim Obeid, Javier Pizones, Frank Kleinstueck, Francisco Javier Sanchez Perez-Grueso, Ferran Pellise, Ahmet Alanay, Erkay Savas, Cetin Bagci, Osman Ugur Sezerman

“…Machine learning (ML) refers to algorithms (often models) that are learned directly from data, germane to past experience. …”
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Safety of creatine supplementation: a scientometrics analysis on the impact of the ‘Creatine For Health’ initiative and introduction to CREAS by Diego A. Bonilla, Drew E. Gonzalez, Gustavo Humeres, Jisun Chun, Kelly Hines, Adriana Gil, Richard B. Kreider

“…We employed supervised machine learning for sentiment analysis to detect and classify subjective content, using the SentiStrength algorithm within the Academic Research version of Mozdeh software. …”
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Knowledge, information needs and behavior regarding HIV and sexually transmitted infections among migrants from sub-Saharan Africa living in Germany: Results of a participatory hea... by Carmen Koschollek, Anna Kuehne, Johanna Müllerschön, Stephen Amoah, Helene Batemona-Abeke, Taty Dela Bursi, Pierre Mayamba, Adama Thorlie, Christina Mputu Tshibadi, Virginia Wangare Greiner, Viviane Bremer, Claudia Santos-Hövener

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Development and external validation of a nomogram prediction model based on quantitative coronary angiography for predicting ischemic lesions: a multi-centre study by Shuai Yang, Shuai Yang, Shuang Leng, Shuang Leng, Zhouchi Wang, Jiang Ming Fam, Jiang Ming Fam, Adrian Fatt Hoe Low, Adrian Fatt Hoe Low, Ru-San Tan, Ru-San Tan, Ping Chai, Ping Chai, Lynette Teo, Lynette Teo, Chee Yang Chin, Chee Yang Chin, John C. Allen, Mark Yan-Yee Chan, Mark Yan-Yee Chan, Khung Keong Yeo, Khung Keong Yeo, Aaron Sung Lung Wong, Aaron Sung Lung Wong, Soo Teik Lim, Soo Teik Lim, Qinghua Wu, Liang Zhong, Liang Zhong, Liang Zhong

“…For per-patient analysis, the corresponding values were 85.8%, 85.7%, 86.0% in the development cohort and 82.2%, 83.3%, 81.1% in the validation cohort.ConclusionThe nomogram may be useful for predicting ischemic lesions using QCA measurements and the LASSO regression algorithm, with external validation indicating potential predictive value in cardiology care settings.…”
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