Identifying patterns of high intraoperative blood pressure variability in noncardiac surgery using explainable machine learning: a retrospective cohort study by Zheng Zhang, Jian Wu, Yi Duan, Linwei Liu, Yaru Liu, Jinghan Wang, Li Xiao, Zhifeng Gao

“…SHapley Additive exPlanations (SHAP) values were used to interpret model outputs and assess feature importance.Results Among 47,520 noncardiac surgeries, 1,996 (4.2%) were classified as HIBPV. …”
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Predicting 24-hour intraocular pressure peaks and averages with machine learning by Ranran Chen, Jinming Lei, Yujie Liao, Yiping Jin, Xue Wang, Xiaomei Li, Danping Wu, Hong Li, Yanlong Bi, Haohao Zhu

“…Predictive models based on five machine learning algorithms were trained and evaluated. …”
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EDMF: A New Benchmark for Multi-Focus Images with the Challenge of Exposure Difference by Hui Li, Tianyu Shen, Zeyang Zhang, Xuefeng Zhu, Xiaoning Song

“…This approach enables the network to effectively learn focus features during training, resulting in clear fused images that align with human visual perception. …”
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Use of computer vision analysis for labeling inattention periods in EEG recordings with visual stimuli by Dmitry Yu Isaev, Samantha Major, Kimberly L. H. Carpenter, Jordan Grapel, Zhuoqing Chang, Matias Di Martino, David Carlson, Geraldine Dawson, Guillermo Sapiro

“…We extract computer vision-based features such as head pose, gaze, and face landmarks from the video of the participant, and train the machine learning model (multi-layer perceptron) on an initial dataset, then adapt it with a small subset of data from a new participant. …”
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AI-enhanced automation of building energy optimization using a hybrid stacked model and genetic algorithms: Experiments with seven machine learning techniques and a deep neural net... by Mohammad H. Mehraban, Samad ME Sepasgozar, Alireza Ghomimoghadam, Behrouz Zafari

“…Unlike the common practices, the scenario development and building optimization tend to be enhanced by using AI in the present paper, using a Python-based script alongside the Non-dominated Sorting Genetic Algorithm (NSGA-II) through EnergyPlus simulations. …”
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Usability and Effectiveness of eHealth and mHealth Interventions That Support Self-Management and Health Care Transition in Adolescents and Young Adults With Chronic Disease: Syste... by ZhiRu Li, FangYan Lu, JingYun Wu, RuiJie Bao, YuXin Rao, Yun Yang, Huafen Wang

“…The interventions ranged from simple text messages to complex interventions involving web-based games and engagement of health care providers, which were summarized into 6 themes: medication monitoring and reminders, symptom tracking and monitoring, management goal setting, knowledge education and self-management skills training, incentives and reinforcement, and communication. …”
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RPL5 NOVEL MUTATION IN A PATIENT WITH DIAMOND BLACKFAN ANEMIA by Metin Çil

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Detection and localization of indigenous economic grasses in depth-color close-range aerial images, using a novel trainingless data-to-decision approach (DIKD Hierarchy), for the S... by Radhwan Sani, Tamer Rabie, Ali Cheaitou

“…The proposed DIKD approach detected the target species with an average accuracy of 0.98, using novel blob features: blob regularity and blob strawness. Experimental results demonstrate the robustness of these features for target plants detection under open environment conditions. …”
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Research on a PTSD Risk Assessment Model Using Multi-Modal Data Fusion by Youxi Luo, Yucui Shang, Dongfeng Zhu, Tian Zhang, Chaozhu Hu

“…For multi-modal data fusion, two sets of solutions are proposed: the first is to extract EEG features using B-spline basis functions, combined with questionnaire data, to construct a multi-modal Zero-Inflated Poisson regression model; the second is to build a multi-modal deep neural network fusion prediction model to automatically extract and fuse multi-modal data features. …”
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Prediction of Omicron Virus Using Combined Extended Convolutional and Recurrent Neural Networks Technique on CT-Scan Images by Anand Kumar Gupta, Asadi Srinivasulu, Kamal Kant Hiran, Goddindla Sreenivasulu, Sivaram Rajeyyagari, Madhusudhana Subramanyam

“…To overcome the drawbacks of the existing system, this research proposes a combined research model that is ECNN-ERNN, where ECNN is used for the extraction of deep features and ERNN is used for exploration using extracted features. …”
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CC-Former: Urban Flood Mapping from InSAR Coherence with Vision Transformer: Libya and Storm Daniel as Test Case by T. Saleh, T. Saleh, T. Saleh, S. Holail, M. Al-Saad, F. Xu, M. Zahran, G.-S. Xia, G.-S. Xia

“…Additionally, we propose a coherence-based scaling (CoBS) module designed to focus on the acquired coherence features of urban flood classes and mitigate the imbalanced distribution of training classes. …”
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Spectroscopic Ages for 4 Million Main-sequence Dwarf Stars from LAMOST DR10 Estimated with a Data-driven Approach by Jia-Hui Wang, Maosheng Xiang, Meng Zhang, Ji-Wei Xie, Jian Ge, Jinghua Zhang, Lanya Mou, Ji-Feng Liu

“…We then train a data-driven model to infer age from their spectra with the XGBoost algorithm. …”
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Understanding Patient and Physiotherapist Requirements for a Personalized Automated Smartphone Telemonitored App for Posttotal Knee Arthroplasty Rehabilitation: Qualitative Study by Eleanor Shuxian Chew, Aileen Eugenia Scully, Samanth Shi-Man Koh, Ee-Lin Woon, Juanita Krysten Miao-Shi Low, Yu-Heng Kwan, John Wei-Ming Tan, Yong-Hao Pua, Celia Ia-Choo Tan, Luke Jonathan Haseler

“…A personalized smartphone-based automated program could be a cost-effective alternative. …”
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Pedagogical conditions for forming the project competence of future teachers in the university environment by Olga Yu. Muller

“…The developed additional course can be applied in the practice of teaching universities in order to improve the quality of professional training of future teachers. The experimental base of the study was the budgetary institution of higher education Surgut State University. …”
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Lobectomy vs total thyroidectomy for unilateral papillary thyroid carcinoma with ipsilateral cervical lymph node metastasis by Shijia Zhang, Shijia Zhang, Kehui Zhou, Kehui Zhou, Jinyu Wang, Ming Zhao, Xiaochun Mao, Jinbiao Shang, Xiabin Lan, Xiabin Lan

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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

“…Second, we compare the gain values of the target and substitute models’ features. Third, we provide an in-depth analysis to check the inclusion of target model split points in substitute models with a heatmap. …”
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Exploration of the relationships between the information and communication technology (ICT) and the education system in Morocco by Abdelkarim Taam, Amine Amar, Brahim Hmedna, Khalid Benabbes, El Menzhi Kaoutar, Rachid Daoudi, Adil El Makrani

“…To understand the perception, our paper is based on testing the statistical association between different features such as the age, the gender or the experience and the use of ICTs and learning approaches. …”
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High spatial resolution crop type and land use land cover classification without labels: A framework using multi-temporal PlanetScope images and variational Bayesian Gaussian mixtu... by Minh Tri Le, Khuong H. Tran, Phuong D. Dao, Hesham El-Askary, Tuyen V. Ha, Taejin Park

“…The VBGMM, unlike the traditional unsupervised classification methods, (1) first estimated optimal parameters that are most suitable based on the input features and then (2) assigned pixels to the cluster with maximum posteriori probability of a mixture of several Gaussian distributions. …”
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Prevention and Rehabilitation of the Athletic Hamstring Injury by Adriana Geraci, P.T., D.P.T., Delaney Mahon, P.T., D.P.T., Eric Hu, B.S., Jesus E. Cervantes, B.S., Shane J. Nho, M.D., M.S.

“…The purpose of this article is to summarize the different features and evaluation of hamstring injuries in athletes, highlight evidence-based rehabilitation interventions, and identify preventative strategies to effectively and efficiently treat athletes, particularly baseball players, with hamstring injuries. …”
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Readiness of future teachers to work at school: Review of theoretical and empirical research by L. A. Novopashina, E. G. Grigorieva, N. F. Ilyina, I. А. Bidus

“…The results obtained make it possible to develop a comprehensive interdisciplinary model of future teachers’ readiness to work at school, considering all the changes and challenges of an information and technologically advanced society.Practical significance is due to the possibility of using the results obtained in the development of ed­ucational programmes in pedagogical training. Based on the data obtained, future researchers and teach­ers can conduct a meta-analysis, qualitative and quantitative assessment of readiness for professional pedagogical activity. …”
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