From Disruption to Reconstruction: Implementing Peer Support in Homelessness During Times of Crisis for Health and Social Care Services by Mathieu Isabel, Daniel Turgeon, Émilie Lessard, Andreea-Cătălina Panaite, Gwenvaël Ballu, Odile-Anne Desroches, Ghislaine Rouly, Antoine Boivin

“…Results: Three main learning points are of interest regarding implementation: 1) crises can precipitate challenges but also particular opportunities for the implementation of peer support initiatives in homelessness; 2) even during a crisis, certain key steps cannot be skipped when the goal is a successful implementation; and 3) research can be an external asset for clinical teams as they struggle to deliver care during periods of crisis. …”
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Feature selection enhances peptide binding predictions for TCR-specific interactions by Hamid Teimouri, Hamid Teimouri, Zahra S. Ghoreyshi, Zahra S. Ghoreyshi, Anatoly B. Kolomeisky, Anatoly B. Kolomeisky, Anatoly B. Kolomeisky, Jason T. George, Jason T. George, Jason T. George, Jason T. George

“…A broad range of physicochemical properties, including amino acid composition, dipeptide composition, and tripeptide features, were integrated into the machine learning-based feature selection framework to identify key properties contributing to binding affinity.ResultsOur analysis reveals that leveraging optimized feature subsets not only simplifies the model complexity but also enhances predictive performance, enabling more precise identification of TCR peptide interactions. …”
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Fusion Model Using Resting Neurophysiological Data to Help Mass Screening of Methamphetamine Use Disorder by Chun-Chuan Chen, Meng-Chang Tsai, Eric Hsiao-Kuang Wu, Shao-Rong Sheng, Jia-Jeng Lee, Yung-En Lu, Shih-Ching Yeh

“…Forty-six patients with MUD and 26 healthy controls were recruited and machine learning methods were employed to systematically compare the classification results of different fusion models. …”
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Developing clinical reasoning along the cognitive continuum: a mixed methods evaluation of a novel Clinical Diagnosis Assessment by Lucinda E. Ainge, Amanda K. Edgar, Jacqueline M. Kirkman, James A. Armitage

“…Therefore, we designed the Clinical Diagnosis Assessment, an assessment for learning, to explicitly train Type 1 and Type 2 reasoning skills in optometry students. …”
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Novel immune cross-talk between inflammatory bowel disease and IgA nephropathy by Qianqian Yan, Zihao Zhao, Dongwei Liu, Jia Li, Shaokang Pan, Jiayu Duan, Zhangsuo Liu

“…Next, multiple machine learning models were applied to confirm the optimal cross-talk genes. …”
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Developing a medication-safety self-assessment tool for rural primary care units - a case from Finnish Lapland by Päivi Sova, Ercan Celikkayalar, Sami Sneck, Anna-Riia Holmström

“…The included 144 statements were divided into 12 thematic sub-groups: (1) Patient information, (2) Drug information, (3) Communication of drug orders and other drug information; (4) Drug labeling, packaging and nomenclature; (5) Drug storage and distribution, (6) Medication device acquisition and use, (7) Environmental factors, workflow and staffing patterns; (8) Staff competency and education, (9) Patient education, (10) Preventive risk management, 11. Learning from medication safety incidents, and 12. …”
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Current update on surgical management for spinal tuberculosis: a scientific mapping of worldwide publications by Romaniyanto Romaniyanto, Muhana Fawwazy Ilyas, Aldebaran Lado, Daffa Sadewa, Daffa Sadewa, Dykall Naf'an Dzikri, Enrico Ananda Budiono, Enrico Ananda Budiono

“…The recent phase reflects a shift towards technology-driven approaches, including minimally invasive techniques, artificial intelligence, and machine learning. China emerged as the leading country with the most contributions based on author, affiliations, funding sponsors, and countries. …”
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The Application of an Intelligent <i>Agaricus bisporus</i>-Harvesting Device Based on FES-YOLOv5s by Hao Ma, Yulong Ding, Hongwei Cui, Jiangtao Ji, Xin Jin, Tianhang Ding, Jiaoling Wang

“…The FES-YOLOv5s deep learning target detection model was used to accurately identify and locate <i>Agaricus bisporus</i>. …”
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A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD by Saeedeh Komijani, Dipak Ghosal, Manpreet K. Singh, Julie B. Schweitzer, Julie B. Schweitzer, Prerona Mukherjee, Prerona Mukherjee

“…We utilized a hierarchical clustering technique to mitigate these collinearity issues and implemented a non-parametric machine learning (ML) model to predict the significance of symptom relations over time. …”
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Research through service: Meeting Chinese international college students’ mental health needs by Changming Duan, Jingru Chen, Fenglan Li, Mi Zhou, Xiubin Lin, Shengnan Li

“…This study adopted a research-through-service approach to design, implement, and evaluate a four-week group intervention program aimed at enhancing the mental health and well-being of CICS.Methods and intervention programThe group intervention was designed with the perspective that effective mental health services for CICS should be culturally specific, growth-oriented, and focused on promoting positive learning outcomes rather than merely addressing problems or solutions. …”
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Automated and code-free development of a risk calculator using ChatGPT-4 for predicting diabetic retinopathy and macular edema without retinal imaging by Eun Young Choi, Joon Yul Choi, Tae Keun Yoo

“…The performance of the ChatGPT-4 developed models was comparable to those created using various machine-learning tools. Conclusion By utilizing ChatGPT-4 with code-free prompts, we overcame the technical barriers associated with using coding skills for developing prediction models, making it feasible to build a risk calculator for DR and DME prediction. …”
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Integrating microplastic research in sustainable agriculture: Challenges and future directions for food production by Marcelo Illanes, María-Trinidad Toro, Mauricio Schoebitz, Nelson Zapata, Diego A. Moreno, María Dolores López-Belchí

“…Furthermore, machine learning algorithms can be employed to analyze complex datasets, enhancing our ability to predict the impacts of MPs on plant health and crop performance under different environmental conditions. …”
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Assessing the Impact of Traffic Emissions on Fine Particulate Matter and Carbon Monoxide Levels in Hanoi through COVID-19 Social Distancing Periods by Nhung H. Le, Bich-Thuy Ly, Phong K. Thai, Gia-Huy Pham, Ich-Hung Ngo, Van-Nguyet Do, Thuy T. Le, Luan V. Nhu, Ha Dang Son, Yen-Lien T. Nguyen, Duong H. Pham, Tuan V. Vu

“…To overcome this challenge, weather normalized concentrations of those pollutants were estimated using the random forest model, a machine learning technique. The normalized weather concentrations showed smaller reductions by 7–10% for PM2.5 and 5–11% for CO, indicating the presence of favorable weather conditions for better air quality during the social distancing period. …”
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Diagnostic accuracy of artificial intelligence algorithms to predict remove all macroscopic disease and survival rate after complete surgical cytoreduction in patients with ovarian... by Somayyeh Noei Teymoordash, Hoda Zendehdel, Ali Reza Norouzi, Mahdis Kashian

“…Most studies agree that Artificial Neural Networks (ANN) and Machine Learning (ML) models outperform conventional statistics in predicting postoperative outcomes.…”
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Digital leadership in quantity surveying: unveiling key characteristics and their role in driving digital transformation by Darren Vermaak, Gerrit Crafford

“…The study suggests fostering a learning culture, encouraging innovation, and instilling a sense of urgency in embracing digital changes. …”
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11 Key Strategies in Using AI Chat GPT to Develop HOTS-Based Entrepreneurship Questionnaires by Almaida Vebibina, Rusijono Rusijono, Andi Mariono, Ahsan Muafa, Dydik Kurniawan, Ragil Sugeng Dewantoro, Dian Noer Asyari, Sussi Widiastuti, Jarot Suseno

“…This research is proposed based on the background of various obstacles in the use of Chat GPT to develop an effective questionnaire that meets the learning objectives. To bridge the gap, this study explores the potential of Chat GPT in crafting assessment questions that focus on higher-order thinking by utilizing existing strategies to enhance critical, analytical, creative and problem-solving thinking in entrepreneurship education. …”
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Predicting exacerbation of renal function by DNA methylation clock and DNA damage of urinary shedding cells: a pilot study by Akihito Hishikawa, Erina Sugita Nishimura, Norifumi Yoshimoto, Ran Nakamichi, Eriko Yoshida Hama, Wataru Ito, Tomomi Maruki, Kengo Nagashima, Ryoko Shimizu-Hirota, Hiromasa Takaishi, Hiroshi Itoh, Kaori Hayashi

“…Abstract Recent reports have shown the feasibility of measuring biological age from DNA methylation levels in blood cells from specific regions identified by machine learning, collectively known as the epigenetic clock or DNA methylation clock. …”
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A Hybrid Fuzzy Wavelet Neural Network Model with Self-Adapted Fuzzy c-Means Clustering and Genetic Algorithm for Water Quality Prediction in Rivers by Mingzhi Huang, Di Tian, Hongbin Liu, Chao Zhang, Xiaohui Yi, Jiannan Cai, Jujun Ruan, Tao Zhang, Shaofei Kong, Guangguo Ying

“…A self-adapted fuzzy c-means clustering was used to determine the number of fuzzy rules. A hybrid learning algorithm based on a genetic algorithm and gradient descent algorithm was employed to optimize the network parameters. …”
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Nursing management in the fever clinic in a general hospital under the normalization of prevention and control of COVID-19 (新型冠状病毒肺炎疫情常态化防控期间综合医院发热门诊护理管理实践)... by YAN Junjie (闫俊杰), QI Wenjing (綦文婧), LI Jia (李佳), WANG Meiyu (王美玉)

“…Efforts were made in the following areas such as reorganization of fever clinics, improvement and implementation of the nosocomial infection control system, preparation of relevant medical staff, enhancement of training and assessment, reinforcement learning of relevant regulations and documents, implementation of prevention and control measures, and nursing team building. …”
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In Situ Classification of Original Rocks by Portable Multi-Directional Laser-Induced Breakdown Spectroscopy Device by Mengyang Zhang, Hongbo Fu, Huadong Wang, Feifan Shi, Saifullah Jamali, Zongling Ding, Bian Wu, Zhirong Zhang

“…This device built upon a previous multi-directional optimization scheme and integrated machine learning to classify seven types of original rock samples: mudstone, basalt, dolomite, sandstone, conglomerate, gypsolyte, and shale from oil logging sites. …”
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