A novel gene signature for predicting outcome in colorectal cancer patients based on tumor cell-endothelial cell interaction via single-cell sequencing and machine learning by Lina Pang, Qingxia Sun, Wenyue Wang, Mingjie Song, Ying Wu, Xin Shi, Xiaonan Shi

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A Comparison of Machine Learning-Based Approaches in Estimating Surface PM_2.5 Concentrations Focusing on Artificial Neural Networks and High Pollution Events by Shijin Wei, Kyle Shores, Yangyang Xu

Subjects: “…machine learning…”
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Machine learning models for dementia screening to classify brain amyloid positivity on positron emission tomography using blood markers and demographic characteristics: a retrospective observational study by Noriyuki Kimura, Kotaro Sasaki, Teruaki Masuda, Takuya Ataka, Mariko Matsumoto, Mika Kitamura, Yosuke Nakamura, Etsuro Matsubara

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Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of Grapevines by Ronald P. Dillner, Maria A. Wimmer, Matthias Porten, Thomas Udelhoven, Rebecca Retzlaff

“…To address these problems, based on a standardized growth class assessment, labeled ground truth data of precisely located grapevines were predicted with specifically selected Machine Learning (ML) classifiers (Random Forest Classifier (RFC), Support Vector Machines (SVM)), utilizing multispectral UAV (Unmanned Aerial Vehicle) sensor data. …”
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Corrigendum to “Constraint-incorporated deep learning model for predicting heat transfer in porous media under diverse external heat fluxes” [Energy and AI 18 (2024) 100425] by Ziling Guo, Hui Wang, Huangyi Zhu, Zhiguo Qu

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When Technology Meets Anxiety:The Moderating Role of AI Usage in the Relationship Between Social Anxiety, Learning Adaptability, and Behavioral Problems Among Chinese Primary School Students by Ma G, Tian S, Song Y, Chen Y, Shi H, Li J

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A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study. by Ilaria Amodeo, Giorgio De Nunzio, Genny Raffaeli, Irene Borzani, Alice Griggio, Luana Conte, Francesco Macchini, Valentina Condò, Nicola Persico, Isabella Fabietti, Stefano Ghirardello, Maria Pierro, Benedetta Tafuri, Giuseppe Como, Donato Cascio, Mariarosa Colnaghi, Fabio Mosca, Giacomo Cavallaro

“…We propose applying Machine Learning (ML), and Deep Learning (DL) approaches to fetuses and newborns with CDH to develop forecasting models in prenatal epoch, based on the integrated analysis of clinical data, to provide neonatal PH as the first outcome and, possibly: favorable response to fetal endoscopic tracheal occlusion (FETO), need for Extracorporeal Membrane Oxygenation (ECMO), survival to ECMO, and death. …”
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Peningkatan Keterampilan Proses Sains dan Pemahaman Konsep melalui Model Learning Cycle 5E Berbantuan Virtual Lab pada Materi Usaha dan Energi by Nora Ilfira Yulasti, Nyoman Rohadi, Desy Hanisa Putri

“…Kata kunci : Aktivitas Siswa, Keterampilan Proses Sains, Pemahaman Konsep, Model Learning Cycle 5E, Virtual Lab. …”
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PENINGKATAN MOTIVASI DAN PRESTASI BELAJAR BIOLOGI KELAS X-7 SMA N 1 BARAT MELALUI PENERAPAN MODEL THINK PAIR SHARE by Nunuk Purwanti

Subjects: “…motivation to learn…”
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Anxiety and engagement in the online classroom: A case study of Thai learners of Chinese as a foreign language by Pairin Srisinthon

Subjects: “…online learning anxiety…”
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The System of Additional Professional Education of the University as a Platform for Implementation of the Federal Project «New Opportunities for Everyone» by M. F. Galikhanov, V. V. Kondratyev, D. V. Elizarov, L. T. Miftakhutdinova

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Harnessing artificial intelligence for predicting breast cancer recurrence: a systematic review of clinical and imaging data by Jaqueline Alvarenga Silveira, Alexandre Ray da Silva, Mariana Zuliani Theodoro de Lima

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Pengaruh Problem-Based Learning terhadap Hasil Belajar Matematika ditinjau dari Kemampuan Berpikir Kritis Siswa SD Kelas V di Kecamatan Cibinong Kabupaten Bogor by Irawati Irawati, Suroyo Suroyo, Idha Novianti

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Advanced matter-element extension model and machine learning for source-specific probabilistic health risk assessment of heavy metals/metaloids in soil-rose systems in Kushui, Northwest China by Jun Li, Li-Bang Ma, Jun-Zhuo Liu, Xu Li, Yun-Qin Yang, Xi-Sheng Tai, Fa-Yuan Zhou, Fei Zang

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The Evaluation of the Successful Integration Implementation of Academic Information System I-Gracias and CeLOE Learning Management System at Telkom University Using DeLone and McLean Model by Miftah Ramadhan, Buce Trias Hanggara, Widhy Hayuhardhika Nugraha Putra

“… Telkom University has implemented data integration on the I-Gracias Academic Information System with the CeLOE Learning Management System (LMS) to make it easier for students to carry out the course registration process. …”
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Rapid detection of carbapenem-resistant Escherichia coli and carbapenem-resistant Klebsiella pneumoniae in positive blood cultures via MALDI-TOF MS and tree-based machine learning models by Xiaobo Xu, Zhaofeng Wang, Erjie Lu, Tao Lin, Hengchao Du, Zhongfei Li, Jiahong Ma

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Data-Driven Bearing Fault Diagnosis of Microgrid Network Power Device Based on a Stacked Denoising Autoencoder in Deep Learning and Clustering by Fast Search without Data Labels by Fan Xu, Xin Shu, Xin Li, Xiaodi Zhang

“…In this paper, we use the stacked denoising autoencoder (SDAE) model in deep learning to construct HI directly from the microgrid power equipment of raw signals in bearings. …”
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Barriers and enablers to recruiting participants within paediatric perioperative and anaesthetic settings: lessons learned from a trial of melatonin versus midazolam in the premedication of anxious children (the MAGIC trial) by Marie C. Hyslop, Diana E. Papaioannou, Robert Bolt, Matthew J. Wilson, Michael Bradburn, Janet Clarkson, Esther Herbert, Nicholas Ireland, Jennifer Kettle, Amanda Loban, Amy C. Norrington, Christopher Vernazza, Christopher Deery

“…The MAGIC trial highlighted variations within anaesthetic practice at individual, local, and regional levels. Lessons learned from the MAGIC trial identifies specific barriers to paediatric trial enrolment, offer solutions and discusses ongoing challenges. …”
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Pre-screening of endomysial microvessel density by fast random forest image processing machine learning algorithm accelerates recognition of a modified vascular network in idiopathic inflammatory myopathies by Alessandro Massaro, Gerardo Cazzato, Giuseppe Ingravallo, Nadia Casatta, Carmelo Lupo, Angelo Vacca, Florenzo Iannone, Francesco Girolamo

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