Enhancement and evaluation for deep learning-based classification of volumetric neuroimaging with 3D-to-2D knowledge distillation by Hyemin Yoon, Do-Young Kang, Sangjin Kim

“…Our proposed method includes three modules: (i) a 3D teacher network that encodes volumetric prior knowledge from the 3D dataset, (ii) a 2D student network that encodes partial volumetric information from the 2D dataset, and aims to develop an understanding of the original volumetric imaging, and (iii) a distillation loss introduced to reduce the gap in the graph representation expressing the relationship between data in the feature embedding spaces of (i) and (ii), thereby enhancing the final performance. …”
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Enhanced Classification of Phonocardiograms Using Modified Deep Learning by Awais Mahmood, Habib Dhahri, Mousa Alhajlah, Abdulaziz Almaslukh

“…Instead of handicraft features, we converted the speech files into spectrograms and then fed them to the Convolutional neural network (CNN) model as images. The innovative approach involves a modified CNN integrated with dual classifiers: a SoftMax classifier and a Support Vector Machine (SVM), The proposed model demonstrates remarkable proficiency, achieving 97.85% accuracy with the SoftMax classifier and 98.28% accuracy with the SVM, surpassing the former. …”
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ReLTER: An R interface for environmental observation in long term ecological research by Alessandro Oggioni, Micha Silver, Paolo Tagliolato, Arnon Karnieli

“…More than forty functions have been implemented that allow the retrieval of species occurrence data from third-party online networks, such as GBIF, iNaturalist, and OBIS, as well as earth observation images from various internet archives, and to harmonize the downloaded data (in terms of structure, semantics, taxonomy, etc.) for combining and linking them in subsequent analyses. …”
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Assessment of economic well-being in South Africa based on remote sensing transfer learning by L. Wang, L. Wang, T. Long, T. Long, E. Adam

“…However, comprehensive and spatially clear data on environmental conditions and socio-economic well-being remain scarce, preventing a thorough analysis of intersecting inequalities. …”
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Kompetencje kluczowe w rozwoju przyszłej kariery zawodowej pokolenia Z a edukacja by Katarzyna Jagielska

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60 Investigating sociodemographic influence on trauma exposure and neural alterations in young adults by Abigail Bossa, Claire Marino, Caitlin Sharp, Tanya Garg, Shreya Bavdekar, Mary Halvorsen, Benjamin Suzrez-Jimenez

“…It also seeks to explore functional connectivity and neural network patterns associated with trauma by analyzing resting state magnetic resonance imaging (MRI) data. …”
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Trajectories of human brain functional connectome maturation across the birth transition. by Lanxin Ji, Iris Menu, Amyn Majbri, Tanya Bhatia, Christopher J Trentacosta, Moriah E Thomason

“…Yet, we presently lack rigorous examination of the longitudinal emergence of human brain functional networks over the birth transition. Leveraging a large, longitudinal perinatal functional magnetic resonance imaging (fMRI) data set, this study models developmental trajectories of brain functional networks spanning 25 to 55 weeks of post-conceptual gestational age (GA). …”
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Remote Assistance for Bone-Fractured Patients using Deep Learning Models by Nallakaruppan Kailasanathan, Sivaramakrishnan Somayaji, Mohamed Baza, Gautam Srivastava, SenthilKumaran Ulaganathan, Gokul Yenduri, Vaishali Ravindranath, Maazen Alsabaan

“…This becomes particularly difficult in emergencies when rapid analysis of medical records is needed, especially if the data is stored on secure blockchain networks. …”
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Applications of artificial intelligence in neurosurgical education: a scoping review by Hector Julio Piñera-Castro, Christian Borges-García

“…Other innovations included AI-generated academic content, neuroanatomical segmentation, and instrument pattern analysis. Ethical concerns highlighted risks of overreliance, image-processing limitations, and the irreplaceable role of clinical intuition. …”
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Preliminary Study of Airfoil Design Synthesis Using a Conditional Diffusion Model and Smoothing Method by Kazuo Yonekura, Yuta Oshima, Masaatsu Aichi

“…In this study, we applied a conditional diffusion model to the design synthesis and showed that the output of this diffusion model contains noisy data caused by Gaussian noise. We show that we can conduct flow analysis on the generated data by using smoothing filters.…”
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Mediator effects of customers’ attitude on factors influencing intention to purchase organic beverages in Vietnam by Dinh Duc Truong, Tran Thi Lan Huong

“…Data are analyzed using AMOS software with descriptive statistics, Cronbach’s alpha test, confirmatory factor analysis, and structural equation modeling. …”
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Evaluation of Efficacy of Artificial Intelligence in Orthopantomogram in Detecting and Classifying Radiolucent Lesions by Sheetal Singar, Ajay Parihar, Prashanthi Reddy

“…The evaluation of the performance of both CNN by new data consisting (60 OPG images) 30 benign and 30 malignant lesions. …”
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In search of knowledge and skills in the area of business models as social innovation in enterprise by Ludmiła Walaszczyk, Elmo de Aangelis, Mojca Vucovič, Gabriela Vlčkova, Evanthia BATZOGIANNI, Beata Belina

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A multitask framework based on CA-EfficientNetV2 for the prediction of glioma molecular biomarkers by Qian Xu, Feng Ning Liang, Ya Ru Cao, Jin Duan, Teng Cui, Teng Zhao, Hong Zhu

“…Accurate, non-invasive prediction of these biomarkers using MRI is of significant clinical value.Materials and methodsWe proposed a novel multitask deep learning framework based on Coordinate Attention-EfficientNetV2 (CA-EfficientNetV2) to simultaneously predict IDH mutation and MGMT promoter methylation status based on MRI data. Initially, unlabeled MR images were annotated using K-means clustering to generate pseudolabels, which were subsequently refined using a Vision Transformer (ViT) network to improve labeling accuracy. …”
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Research Advances in Underground Bamboo Shoot Detection Methods by Wen Li, Qiong Shao, Fan Guo, Fangyuan Bian, Huimin Yang

“…To address these, an integrated intelligent framework is proposed: (1) three-dimensional modeling via multi-sensor fusion for subsurface mapping; (2) artificial intelligence (AI)-driven harvesting robots with adaptive excavation arms and obstacle avoidance; (3) standardized cultivation systems to optimize soil conditions; (4) convolution neural network–transformer hybrid models for visual-aided radar image analysis; and (5) aeroponic AI systems for controlled growth monitoring. …”
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Quantitative estimation method for complex part surface defects based on multimodal information fusion by Rui Wang, Wei Du, Qingchao Jiang

“…We enhance the Faster R-CNN network to improve defect localization and feature extraction, establishing a mapping between 2D images and 3D data to pinpoint defect-specific areas accurately. …”
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AI may help to predict thyroid nodule malignancy based on radiomics features from [18F]FDG PET/CT by Krystian Ślusarz, Mikolaj Buchwald, Adrian Szczeszek, Szymon Kupinski, Anna Gramek-Jedwabna, Wojciech Andrzejewski, Juliusz Pukacki, Robert Pękal, Marek Ruchała, Rafał Czepczyński, Cezary Mazurek

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Parkinson’s disease detection using inceptionV3: A Deep learning approach by Pallavi M. Shanthappa, Madhwesh Bayari, G.B. Abhilash, K.V. Gokul, P.J. Ashish

“…The future can be directed towards the combination of spiral images with other biomarkers or a broader data set with other motor measures in a wider disease assessment. • The study focuses on enhancing features extraction by leveraging hybrid deep learning models, improving classification performance. • Implementation of features scaling leads to better model performance, with improved accuracy. • The comparative analysis of CNN architecture provides valuable insights into balancing computational efficiency and classification performance.…”
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Generalization challenges in video deepfake detection: methods, obstacles, and technological advances by LI Junjie, WANG Jianzong, ZHANG Xulong, QU Xiaoyang

“…To address this issue, researchers have proposed various solutions, such as neural network architecture design, multi-tasklearning, new loss functions, data augmentation, innovative training procedures, and the integration of biometric recognition technologies. …”
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ALDP-FL for adaptive local differential privacy in federated learning by Lixin Cui, Xu Wu

“…Regarding the reconstructed images under the iDLG attack, the average improvement rates in MSE and SSIM reach 391.2% and –85.4%, respectively, significantly outperforming all other comparison methods.…”
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