Development and validation of a visual impairment prediction nomogram in chronic kidney diseases: the National Health and Nutrition Examination Survey, 1999-2008 by Yu-He Tan, Jia-Qi Li, Xu-Fang Sun

“…AIM: To develop a nomogram to predict the risk of visual impairment (VI) in patients with chronic kidney disease (CKD). …”
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Telling people where to look in a soccer-based decision task: A nomothetic approach by Daniel Bishop, Gustav Kuhn, Claire Maton

“…Research has shown that identifiable visual search patterns characterize skilled performance of anticipation and decision-making tasks in sport. …”
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Effects of suspension exercise training in the treatment of lumbar disk herniation: a systematic review and meta-analysis by Yu’ang Liu, Silang Huang, Xinxin Zhang, Huangying Liao, Weiguo Liu, Zhi Zhang

“…Suspension exercise training significantly improved the lumbar disk herniation (LDH) visual analog scale (VAS) score (mean difference (MD) = −0.96; 95% confidence interval (CI), −1.10 to-0.82; p < 0.00001, I2 = 23%), the Japanese Orthopedic Association (JOA) score (MD = 3.29, 95% CI, 1.67 to 4.90; p < 0.0001, I2 = 92%), and the Oswestry Disability Index (ODI) score (MD = −5.41, 95% CI, −7.41 to −3.40; p < 0.00001, I2 = 86%). …”
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ReactionT5: a pre-trained transformer model for accurate chemical reaction prediction with limited data by Tatsuya Sagawa, Ryosuke Kojima

“…This study introduces ReactionT5, a transformer-based chemical reaction foundation model pre-trained on the Open Reaction Database—a large publicly available reaction dataset. …”
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A Comparative Study of EmberGen and Blender in Fire Explosion Simulations by Arya Luthfi Mahadika, Ema Utami

“…The advancement of visual effects (VFX) technology has intensified the need for efficient fire explosion simulations across film, gaming, and real-time applications. …”
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Supervised machine learning statistical models for visual outcome prediction in macular hole surgery: a single-surgeon, standardized surgery study by Kanika Godani, Vishma Prabhu, Priyanka Gandhi, Ayushi Choudhary, Shubham Darade, Rupal Kathare, Prathiba Hande, Ramesh Venkatesh

“…Six supervised ML models—ANCOVA, Random Forest (RF) regression, K-Nearest Neighbor, Support Vector Machine, Extreme Gradient Boosting, and Lasso regression—were trained using an 80:20 training-to-testing split. …”
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Evaluating the Efficacy of Cueing Strategies versus Walking Aids in Parkinson’s Disease: An Interventional Study by Sharki Rawat, Jyoti Balyan, Sonia

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Brain Shaped by Music Performance: Cognitive Effects and Genetic Approaches by Emel Güneş, Şayeste Çağıl İnal

“…Cognitive functions such as verbal memory, motor functions, visual and spatial functions, executive functions are some of the cognitive components which are improved with music performance. …”
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Rachel Rosenthal, une artiste écoféministe de la performance by Mylène Ferrand

“…She was a historical figure in performance art, which she helped to create, in connection with her training in classical dance, theater, music and visual arts. …”
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A Novel Cross-Attention-Based Pedestrian Visual–Inertial Odometry With Analyses Demonstrating Challenges in Dense Optical Flow by Ilari Pajula, Niclas Joswig, Aiden Morrison, Nadia Sokolova, Laura Ruotsalainen

“…Recently, dense-optical-flow-based end-to-end trained deep learning VIO models have gained superior performance in outdoor navigation. …”
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Peculiarities of the pedagogical situation at the training of bachelors on the direction 08.03.01 «Construction» on the example of discipline of specialization by Nelli I. Taraseeva

“…The assessment of the nature of the existing links of the learning process performed in the work made it possible to identify the problems and contradictions of the latter.The developed learning technology of mastering the profile discipline takes into account the levels of training and learning that allows creating an effective communication channel “lecturer” – “student”, the successful work of which creates opportunities for solving a large number of methodological problems of teaching and self-study of the course.Conclusion: The analysis of works on pedagogy, psychology, didactics and technology of the educational process performed in the article allowed to develop an effective logical structure of the educational material. …”
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Quantifying optimal inner limiting membrane peeling in macular hole surgery: a machine learning framework for predictive modeling and schematic visualization by Xiang Zhang, Hongjie Ma, Song Lin, Ledong Zhao, Lu Chen, Zetong Nie, Zhaoxiong Wang, Chang Liu, Xiaorong Li, Wenbo Li, Bojie Hu

“…Abstract Purpose Internal limiting membrane (ILM) peeling in macular hole (MH) surgery is critical but challenging, and current practices lack standardized tools for quantifying and visualizing optimal peeling dimensions.This study aimed to develop a machine learning framework to recommend surgeon-specific ILM peeling radius during macular hole surgery, integrating predictive modeling with schematic visualization to guide operative planning. …”
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Construction of a poor prognosis prediction and visualization system for intracranial aneurysm endovascular intervention treatment based on an improved machine learning model by Chunyu Lei, Anhui Fu, Bin Li, Shengfu Zhou, Jun Liu, Yu Cao, Bo Zhou

“…Logistic multivariate analysis was used to validate the selected features. Additionally, a visualization system was developed to automatically calculate the risk level of poor prognosis.ResultsIn the training set, the improved machine learning model achieved a maximum F1 score of 0.8633 and an area under the curve (AUC) of 0.9118. …”
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Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned by Marketa Ciharova, Khadicha Amarti, Ward van Breda, Ward van Breda, Martin J. Gevonden, Sina Ghassemi, Annet Kleiboer, Christiaan H. Vinkers, Christiaan H. Vinkers, Christiaan H. Vinkers, Christiaan H. Vinkers, Milou S. C. Sep, Milou S. C. Sep, Milou S. C. Sep, Milou S. C. Sep, Sophia Trofimova, Alexander C. Cooper, Xianhua Peng, Xianhua Peng, Mieke Schulte, Mieke Schulte, Eirini Karyotaki, Eirini Karyotaki, Eirini Karyotaki, Pim Cuijpers, Pim Cuijpers, Pim Cuijpers, Heleen Riper, Heleen Riper

“…We aimed to detect laboratory-induced stress using multimodal data and identify challenges researchers may encounter when conducting a similar study.MethodsWe conducted a preliminary exploration of performance of a machine-learning algorithm trained on multimodal data, namely visual, acoustic, verbal, and physiological features, in its ability to detect stress severity following a partially automated online version of the Trier Social Stress Test. …”
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MATLAB Application for User-Friendly Design of Fully Convolutional Data Description Models for Defect Detection of Industrial Products and Its Concurrent Visualization by Fusaomi Nagata, Shingo Sakata, Keigo Watanabe, Maki K. Habib, Ahmad Shahrizan Abdul Ghani

“…In particular, a systematic threshold determination method is proposed to obtain the best performance for defect detection from FCDD models. Also, through three different kinds of defect detection experiments, the usefulness and effectiveness of FCDD models in terms of defect detection and its concurrent visualization are quantitatively and qualitatively evaluated by comparing conventional transfer learning-based CNN models.…”
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Steady-State Visual-Evoked-Potential–Driven Quadrotor Control Using a Deep Residual CNN for Short-Time Signal Classification by Jiannan Chen, Chenju Yang, Rao Wei, Changchun Hua, Dianrui Mu, Fuchun Sun

“…In this paper, we study the classification problem of short-time-window steady-state visual evoked potentials (SSVEPs) and propose a novel deep convolutional network named EEGResNet based on the idea of residual connection to further improve the classification performance. …”
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Performance validation of deep-learning-based approach in stool examination by Kristal Dale Felimon Corpuz, Teera Kusolsuk, Benjamaporn Wongphan, Putza Chonsawat, Kaung Myat Naing, Siridech Boonsang, Veerayuth Kittichai, Chia-Kwung Fan, Santhad Chuwongin, Dorn Watthanakulpanich

“…Moreover, the receiver operating characteristic (ROC) and precision-recall (PR) curves were determined for visual comparison. Lastly, Cohen’s Kappa and Bland–Altman analyses were used to statistically measure the significant differences and visualize the association levels between the human experts and the deep learning models’ classification performance in intestinal parasite identification. …”
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SLIP-flood: Soft-combination of Swin Transformer and Lightweight Language-Image Pre-training for Flood Images Classification by Heng Tang, Xiaoping Rui, Jiarui Li, Ninglei Ouyang, Yiheng Xie, Xiaodie Liu, Yiming Bi

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Effective unilateral/bilateral robot-assisted training for upper limb motor function rehabilitation: a cross-sectional study by Guang Feng, Guang Feng, Guohong Chai, Guohong Chai, Jiaji Zhang, Jiaji Zhang, Tao Song, Tao Song, Changcheng Shi, Changcheng Shi, Jialin Xu, Jialin Xu, Guokun Zuo, Guokun Zuo

“…We compared unilateral passive training (UPT), bilateral passive training (BPT), and unilateral active training (UAT) with various feedback types (visual, force, and visual-force, none). …”
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Elevated core temperature in addition to mental fatigue impairs aerobic exercise capacity in highly trained athletes in the heat by Takashi Naito, Tatsuya Saito, Hirotsugu Morinaga, Nobuhiko Eda, Yohei Takai

“…Participants performed the AX-Continuous Performance Task and Stroop Task to induce mental fatigue during a warm water immersion at 40 °C (HYP) and a passive seated heat exposure in a climatic chamber at 35 °C and 60% relative humidity (SKIN) for 45 min before exercise. …”
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