Predicting radiation pneumonitis in lung cancer using machine learning and multimodal features: a systematic review and meta-analysis of diagnostic accuracy by Zhi Chen, GuangMing Yi, XinYan Li, Bo Yi, XiaoHui Bao, Yin Zhang, XiaoYue Zhang, ZhenZhou Yang, Zhengjun Guo

“…By selecting multiple machine learning algorithm frameworks and competing for the best combination model based on research goals, the reliability and accuracy of the radiation pneumonitis prediction model can be greatly improved. …”
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Performance of emergency triage prediction of an open access natural language processing based chatbot application (ChatGPT): A preliminary, scenario-based cross-sectional study by İbrahim Sarbay, Göksu Bozdereli Berikol, İbrahim Ulaş Özturan

“…OpenAI’s ChatGPT is a supervised and empowered machine learning-based chatbot. The aim of this study was to determine the performance of ChatGPT in emergency medicine (EM) triage prediction. …”
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A pilot randomized trial comparing face-to-face and internet-based unified transdiagnostic treatment for adolescents with anxiety and depressive disorders in Iran by Nasim Mousavi, Fereshteh Momeni, Abbas Pourshahbaz, Hamid Poursharifi, Zahra Daneshian, Gerhard Andersson, Gerhard Andersson

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A machine learning model revealed that exosome small RNAs may participate in the development of breast cancer through the chemokine signaling pathway by Jun-luan Mo, Xi Li, Lin Lei, Ji Peng, Xiong-shun Liang, Hong-hao Zhou, Zhao-qian Liu, Wen-xu Hong, Ji-ye Yin

“…Method Peripheral blood samples from breast cancer screening positive and negative people were used for small RNA sequencing of plasma exosomes. …”
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The Wide Swath Significant Wave Height: An Innovative Reconstruction of Significant Wave Heights From CFOSAT’s SWIM and Scatterometer Using Deep Learning by J. K. Wang, L. Aouf, A. Dalphinet, Y. G. Zhang, Y. Xu, D. Hauser, J. Q. Liu

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Intelligent Grinding System for Medium/Thick Plate Welding Seams in Construction Machinery Using 3D Laser Measurement and Deep Learning by Qifeng Liu, Rencheng Zheng, Pengchao Li, Chao Liu, Deyuan Mi, Jian Wang, Wenli Xie

“…This study proposes an intelligent grinding system using 3D line laser measurement and deep learning algorithms to solve the problems of inefficiency and inaccuracy existing in traditional weld grinding methods. …”
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Cognitive-behavioral therapy to normalize social learning for patients with major depressive disorders: study protocol for a single-arm clinical trial by Yuening Jin, Si Zu, Pengchong Wang, Fangrui Sheng, Xue Wang, Yun Wang, Qun Chen, Jie Zhong, Fang Yan, Jia Zhou, Zhanjiang Li, Yuan Zhou

“…Abstract Background The current study aims to explore the efficacy of cognitive behavioral therapy (CBT) in normalizing social learning capabilities and its underlying neural processes among patients with MDD, in terms of enhancing learning towards positive social feedback, and reducing excessive learning towards negative social feedback. …”
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Exploring the ERP trace of task-set control in the composite design task-switching paradigm by Fangyuan Zhou, Zhongjin Tian, Xiangqian Li

“…Previous research has hypothesized that in the composite design task-switching experiments, participants may employ compound retrieval strategies based on associative learning to complete the tasks. …”
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Research on music education simulation based on interactive experience of virtual and reality by Wanchen Li

“…The results show that most students have a positive attitude towards this novel teaching method, and they believe that this method can better stimulate the interest in learning and improve the learning effect. …”
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Feasibility of GPT-3.5 versus Machine Learning for Automated Surgical Decision-Making Determination: A Multicenter Study on Suspected Appendicitis by Sebastian Sanduleanu, Koray Ersahin, Johannes Bremm, Narmin Talibova, Tim Damer, Merve Erdogan, Jonathan Kottlors, Lukas Goertz, Christiane Bruns, David Maintz, Nuran Abdullayev

“…Our objective was to determine whether GPT-3.5, when provided high-throughput clinical, laboratory, and radiological text-based information, will come to clinical decisions similar to those of a machine learning model and a board-certified surgeon (reference standard) in decision-making for appendectomy versus conservative treatment. …”
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The effects of community-based education programs on empathy, emotional intelligence, and caring behaviors among nursing students: a scoping review by Ma Jing, Ma Jing, Pinglei Chui, Mei Chan Chong, Tang Maoting

“…IntroductionCommunity-based learning approaches are gaining recognition in nursing education as a means to address the needs of aging societies by fostering empathy, emotional intelligence, and caring behaviors among nursing students. …”
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Development and validation of a screening tool for sepsis without laboratory results in the emergency department: a machine learning studyResearch in context by Shan Jiang, Shuai Dai, Yulin Li, Xianlong Zhou, Cheng Jiang, Cong Tian, Yana Yuan, Chengwei Li, Yan Zhao

“…We aimed to develop a quick sepsis screening tool (qSepsis) based on patients’ non-laboratory clinical data at the emergency department (ED) using machine learning (ML), and compare its performance with established clinical scores. …”
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El efecto de una combinación de aula invertida y gamificación en la calidad de enseñanza percibida, la satis-facción con la asignatura y el rendimiento académico de los estudiantes... by Ivan Peña Gónzalez, Alejandro Javaloyes, Manuel Moya-Ramón

“…The student’s perceived quality of teaching was higher (6%) than in the previous three courses, especially for questions related to the methodology used during the teaching-learning process and student’s motivation. This suggests that implementing a flipped classroom and gamification strategies positively affects student engagement, motivation, and academic performance, leading to an improvement in teaching quality and satisfaction, and a significant increase in academic performance compared to traditional teaching methods. …”
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Deep Learning Technique for Automatic Segmentation of Proximal Hip Musculoskeletal Tissues From CT Scan Images: A MrOS Study by Mahdi Imani, Jared Buratto, Thang Dao, Erik Meijering, Sara Vogrin, Timothy C. Y. Kwok, Eric S. Orwoll, Peggy M. Cawthon, Gustavo Duque

“…Conclusion Our deep learning–based technique offers a fast and accurate method for segmentation and quantification of musculoskeletal tissues in proximal hip, with potential clinical value.…”
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Surface-Enhanced Raman Scattering Combined with Machine Learning for Rapid and Sensitive Detection of Anti-SARS-CoV-2 IgG by Thais de Andrade Silva, Gabriel Fernandes Souza dos Santos, Adilson Ribeiro Prado, Daniel Cruz Cavalieri, Arnaldo Gomes Leal Junior, Flávio Garcia Pereira, Camilo A. R. Díaz, Marco Cesar Cunegundes Guimarães, Servio Túlio Alves Cassini, Jairo Pinto de Oliveira

“…This work reports an efficient method to detect SARS-CoV-2 antibodies in blood samples based on SERS combined with a machine learning tool. …”
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Opportunities and practices supporting responsive health care for forced migrants: lessons from transnational practice and a mixed-methods systematic review by Amy Robinson, Protus Musotsi, Ziaur Rahman A Khan, Laura Nellums, Bayan Faiq, Kofi Broadhurst, Gisela Renolds, Michael Pritchard, Andrew Smith

“…Design We integrated (1) local stakeholder perspectives, from workshops and dialogue; (2) evidence and knowledge from a mixed-methods systematic review; and (3) learning from five case examples from current international practice. …”
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Determining the Teachers' Attitude towards "Mistake" and "Making Mistakes" in the Learning Process and Improving the Culture facing it (case study: elementary school students) by Mazhar Babaee, Hedyeh Azagh

“…Some teachers have positive and constructive ideas about making mistakes and they see it as an opportunity to learn and as a stepping stone to progress and achieve success. …”
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Identification of green leafhoppers (cicadellidae) in vineyards through an automatic image acquisition system from yellow sticky traps associated with deep-learning by Proença Maria da Conceição, Rebelo Maria Teresa, Valent Riccardo, Mateus Rebeca, Gaspar Pedro Diniz, Lopes Carlos Manuel, Franco José Carlos

“…The deep learning algorithm based on convolutional neural networks (CNNs) learn discriminators from a diverse set of green leafhopper images. …”
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A machine learning model reveals invisible microscopic variation in acute ischaemic stroke (≤ 6 h) with non-contrast computed tomography by Jiahe Tan, Mengjun Xiao, Zhipeng Wang, Shuzhen Wu, Kun Han, Haiyan Wang, Yong Huang

“…Methods This study proposed a machine learning (ML) for infarct detection, enabling automated quantitative assessment of AIS lesions on NCCT images. …”
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A novel Swin transformer based framework for speech recognition for dysarthria by Rabbia Mahum, Ismaila Ganiyu, Lotfi Hidri, Ahmed M. El-Sherbeeny, Haseeb Hassan

“…Several previous studies have concentrated on detecting dysarthria speech using machine learning-based methods. However, the false positive rate is high due to the varying nature of speech and environmental factors such as background noise. …”
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