Digital Quantitative Detection for Heterogeneous Protein and mRNA Expression Patterns in Circulating Tumor Cells by Hao Li, Jinze Li, Zhiqi Zhang, Qi Yang, Hong Du, Qiongzhu Dong, Zhen Guo, Jia Yao, Shuli Li, Dongshu Li, Nannan Pang, Chuanyu Li, Wei Zhang, Lianqun Zhou

“…Importantly, by integrating machine learning, d‐SCOUT allows clustering of CTC characteristics at the mRNA and protein levels, mapping normalized heterogeneous 2D molecular profiles to assess HCC metastatic risk. …”
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Job satisfaction amongst special education teachers by Z. S. Alkayed, S. M. Al Ali, M. M. Al Masa’deh

“…The study contributes to understanding of the factors shaping student teachers’ perspectives and underscores the importance of promoting job satisfaction and positive attitudes among special education teachers to foster a supportive learning environment.                Practical significance of this study is that it provides valuable insights for the field of special education and teacher training. …”
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Effectiveness of flipped classrooms in Chinese students of clinical medicine major undergoing clinical practice: a meta-analysis by Xinrui Sun, Xin Yuan, Linyu Zhang, Yi Zhang, Xue Xiao, Hanmin Liu, Fang Ma

“…While flipped classrooms have gained popularity for their potential to enhance learning outcomes, the effectiveness of this approach in clinical settings remains underexplored. …”
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Improving apgar scores and reducing perineal injuries through midwife-led quality improvements: an observational study in Uganda by Johanna Blomgren, Michael B. Wells, Dinah Amongin, Kerstin Erlandsson, John Wanyama, Diana A. Afrifa, Helena Lindgren

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Trends and Gaps in Digital Precision Hypertension Management: Scoping Review by Namuun Clifford, Rachel Tunis, Adetimilehin Ariyo, Haoxiang Yu, Hyekyun Rhee, Kavita Radhakrishnan

“…The most commonly used digital technologies were mobile phones (33/46, 72%), blood pressure monitors (18/46, 39%), and machine learning algorithms (11/46, 24%). In total, 45% (21/46) of the studies either did not report race or ethnicity data (14/46, 30%) or partially reported this information (7/46, 15%). …”
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Analisis Sistem Pelaksanaan Kelas Ibu Hamil di Puskesmas Malalak dan Biaro Kabupaten Agam by Ayu Nurdiyan, Desmiwarti ., Rizanda Machmud

“…<br />Kata kunci: puskesmas, analisis sistem, kelas ibu hamil</p><p>Abstract<br />Antenatal class is a learning tool for pregnant women to obtain sufficient knowledge to prevent complication, increase coverage of antenatal visits and having child delivery at the health care practitioner. …”
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KMT2C/KMT2D-dependent H3K4me1 mediates changes in DNA replication timing and origin activity during a cell fate transition by Deniz Gökbuget, Liana Goehring, Ryan M. Boileau, Kayla Lenshoek, Tony T. Huang, Robert Blelloch

“…The causal relationships between these features and DNA replication timing (RT), especially during cell fate changes, are largely unknown. Using machine learning, we quantify 21 chromatin features predicting local RT and RT changes during differentiation in embryonic stem cells (ESCs). …”
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Construction of a novel radioresistance-related signature for prediction of prognosis, immune microenvironment and anti-tumour drug sensitivity in non-small cell lung cancer by Yanliang Chen, Chan Zhou, Xiaoqiao Zhang, Min Chen, Meifang Wang, Lisha Zhang, Yanhui Chen, Litao Huang, Junjun Sun, Dandan Wang, Yong Chen

“…The biological functions exerted by the key gene LBH were verified by in vitro experiments.Results Ninety-nine RRRGs were screened by intersecting the results of DEGs and WGCNA, then 11 hub RRRGs associated with survival were identified using machine learning algorithms (LASSO and RSF). Subsequently, an eight-gene (APOBEC3B, DOCK4, IER5L, LBH, LY6K, RERG, RMDN2 and TSPAN2) risk score model was established and demonstrated to be an independent prognostic factor in NSCLC on the basis of Cox regression analysis. …”
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Therapeutic dose prediction using score-based diffusion model for pretreatment patient-specific quality assurance by Xiuwen Yu, Jiabin Lin, Changfei Gong, Minhui Zhang, Xianyu Luo, Qiegen Liu, Yun Zhang

“…Currently, the prediction methods used for prePSQA fall under the category of supervised learning, limiting their generalization ability and resulting in poor performance on new data. …”
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The Influencers and the Adoption of New Products: Model for the Influencer Marketing by Henen Oulhi

“…Key motivations for following influencers include the constant stream of posts, the desire to acquire new products, entertainment, and learning from others’ experiences with the products and their features. …”
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ARES by Josué Miguel de Oliveira, François Isnaldo Dias Caldeira, Lucas Ribeiro Monteiro, Kellen Cristina da Silva Gasque

“…Resultados: Repositórios virtuais e bibliotecas digitais, impulsionados pela popularização da EaD e do e-learning, têm impacto significativo na pesquisa global, mas a acessibilidade ainda é desigual. …”
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Explainable artificial intelligence in web phishing classification on secure IoT with cloud-based cyber-physical systems by Sultan Refa Alotaibi, Hend Khalid Alkahtani, Mohammed Aljebreen, Asma Alshuhail, Muhammad Kashif Saeed, Shouki A. Ebad, Wafa Sulaiman Almukadi, Moneerah Alotaibi

“…This research presents a novel approach to address this problem using machine learning (ML) methods for phishing website classification. …”
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An FPGA-Based SiNW-FET Biosensing System for Real-Time Viral Detection: Hardware Amplification and 1D CNN for Adaptive Noise Reduction by Ahmed Hadded, Mossaad Ben Ayed, Shaya A. Alshaya

“…This attempt combines SiNW-FET biosensing technology with FPGA-implemented deep learning noise reduction, creating a compact system capable of real-time viral detection with minimal computational latency. …”
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Measuring Empathy among Dental Students and Interns: A Cross-Sectional Study from Dammam, Saudi Arabia by Muhammad Nazir, Muhanad Alhareky, Abdulrahman Alqahtani, Leenah Alsulaimi, Reema Alotaibi, Najwa Yousef, Fatimah Abushal, Jehan Alhumaid

“…Empathy should be integrated into dental curricula for effective student learning and positive patient care outcomes.…”
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Alterations of gray matter volume and functional connectivity in patients with cognitive impairment induced by occupational aluminum exposure: a case-control study by Huaxing Meng, Bo Liu, Xiaoting Lu, Yan Tan, Shanshan Wang, Baolong Pan, Hui Zhang, Qiao Niu

“…Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and an auditory-verbal learning test (AVLT). All participants underwent magnetic resonance imaging scans. 3D T1-weighted anatomical images and resting-state functional magnetic resonance imaging data were acquired, and voxel-based morphometry and ROI-based FC were used for analysis. …”
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AI Chatbots and Cognitive Control: Enhancing Executive Functions Through Chatbot Interactions: A Systematic Review by Pantelis Pergantis, Victoria Bamicha, Charalampos Skianis, Athanasios Drigas

“…<b>Conclusions</b>: AI chatbots are an innovative artificial intelligence tool that can function as a digital assistant for learning and expanding executive skills, contributing to the cognitive, metacognitive, and social development of the individual. …”
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Analysis of the growth trajectories of junior residents in Japan: a longitudinal cohort study using data from a nationwide e-portfolio system (EPOC2) by Sachiko Ohde, Takahiro Kiuchi, Makoto Takahashi, MASANAGA YAMAWAKI, Tsuguya Fukui, Tsuyoshi Okuhara, Hiroko Okada, Nobutoshi Nawa, Eriko Okada, Ayako Kashimada, Yu Akaishi, Yujiro Tanaka

“…The study objective is to identify the learning trajectory of junior residents to provide insights into the provision of better postgraduate and undergraduate medical education in Japan.Design Longitudinal cohort study.Setting Hospitals nationwide adopting EPOC2.Participants 7671 residents who participated in clinical training programmes at hospitals adopting EPOC2 between April 2020 and March 2022.Primary outcome measure Formative evaluation scores assessed through self-evaluation by junior residents and evaluations by supervisors/senior physicians at the end of each rotation in each clinical department.Results For all evaluation items, growth trajectories were divided into six groups, each with distinct characteristics based on the specific content of the evaluation form. …”
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Biomarkers troponin and procalcitonin in addition to CRB-65 enhance risk stratification in patients with community-acquired pneumonia by Imrana Farhat, Maciej Rosolowski, Katharina Ahrens, Jasmin Lienau, Peter Ahnert, Mathias Pletz, Gernot Rohde, Jan Rupp, Markus Scholz, Martin Witzenrath, the CAPNETZ Study Group

“…We utilised a machine-learning approach on 800 samples from the German CAPNETZ network (competence network for CAP) to refine risk prediction models combining these biomarkers with the CRB-65 score regarding our defined end-point: death or ICU admission during the current CAP episode within 28 days after study inclusion. …”
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A fast monocular 6D pose estimation method for textureless objects based on perceptual hashing and template matching by Jose Moises Araya-Martinez, Jose Moises Araya-Martinez, Vinicius Soares Matthiesen, Vinicius Soares Matthiesen, Simon Bøgh, Jens Lambrecht, Rui Pimentel de Figueiredo

“…Additionally, we compare our method to state-of-the-art deep learning models on a public dataset. Although our algorithm does not outperform them in absolute accuracy, it provides a more favorable trade-off between accuracy and processing time, which is especially relevant to applications using resource-constrained devices.…”
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Application of MRI image segmentation algorithm for brain tumors based on improved YOLO by Tao Yang, Xueqi Lu, Lanlan Yang, Miyang Yang, Jinghui Chen, Hongjia Zhao

“…ObjectiveTo assist in the rapid clinical identification of brain tumor types while achieving segmentation detection, this study investigates the feasibility of applying the deep learning YOLOv5s algorithm model to the segmentation of brain tumor magnetic resonance images and optimizes and upgrades it on this basis.MethodsThe research institute utilized two public datasets of meningioma and glioma magnetic resonance imaging from Kaggle. …”
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