Familial Hemiplegic Migraine with Severe Attacks: A New Report with ATP1A2 Mutation by E. Martínez, R. Moreno, L. López-Mesonero, I. Vidriales, M. Ruiz, A. L. Guerrero, J. J. Tellería

“…We identified a variant in heterozygous state in ATP1A2 gene (p.Thr364Met), pathogenic according to different prediction algorithms (SIFT, PolyPhen2, MutationTaster, and Condel). …”
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Seamless monitoring of marine heatwaves: capability of gap-filled, geostationary satellite sea surface temperature data by Seonju Lee, Myung-Sook Park

“…Moreover, these seamless SST data serve as inputs for numerical modeling and the deep learning algorithms and has immense potential for both forecasting marine heatwaves and implementing a 24-h continuous monitoring technique. …”
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Polygenic risk score for acute rejection based on donor-recipient non-HLA genotype mismatch. by Rui Cao, David P Schladt, Casey Dorr, Arthur J Matas, William S Oetting, Pamala A Jacobson, Ajay Israni, Jinbo Chen, Weihua Guan

“…Additional work will be needed to understand the role of SNPs included in the PRS and to further improve donor-recipient genetic matching algorithms. Trial registry: Deterioration of Kidney Allograft Function Genomics (NCT00270712) and Genomics of Kidney Transplantation (NCT01714440) are registered on ClinicalTrials.gov.…”
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SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer by Sameh I. Selem, Attia A. El-Fergany, Eid A. Gouda, Mohamed F. Kotb, Islam Ismael

“…The CDO’s convergence patterns and the SOFCs unit’s performance are studied and proved at steady-state by comparing its results to a number of recognized algorithms under varied operating scenarios. A significant SMSE’s values of 3.46 µV2 and 7.38 µV2 are attained at 800οC and 900οC, respectively by the CDO. …”
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Supervised machine learning and genotype by trait biplot as promising approaches for selection of phytochemically enriched Rhus coriaria genotypes by Hamid Hatami Maleki, Reza Darvishzadeh, Ahmad Alijanpour, Yousef Seyfari

“…By using 13 feature selection algorithms, ISSR loci (U823) L1, (U835) L1, (U801) L1, (U816) L2, (U816) L4, (U835) L4, (U854) L1, and (U835) L9 were identified as functional markers which could predict phytochemical response of sumac germplasm. …”
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A Novel AI-Based Integrated Cybersecurity Risk Assessment Framework and Resilience of National Critical Infrastructure by Sardar Muhammad Ali, Abdul Razzaque, Muhammad Yousaf, Sardar Sadaqat Ali

“…This study proposes a novel technique utilizing ML and DL algorithms for threat detection. We began with data preprocessing, which included cleansing the data, addressing missing values through Multiple Imputation by Chained Equations (MICE), and applying transformations such as encoding and standard scaling. …”
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Priority areas of police bodies’ activity in ensuring the citizens’ rights in the conditions of martial law legal regime in Ukraine by O. I. Bezpalova

“…The need to develop effective algorithms for police actions in conditions of active hostilities and in de-occupied territories has been argued, in particular regarding: demining of territories and buildings by investigative-operational groups equipped with mobile forensic laboratories; identification of collaborators and sabotage groups; recording and documenting war crimes depending on their type; investigation of certain types of war crimes; implementation of measures of police custody, taking into account the significant increase in the number of persons who need such measures; inspections of vehicles on highways and roadblocks; searching for missing persons.…”
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Use of machine learning in occupational risk communication for healthcare workers: protocol for scoping review by Gabriela Laudares Albuquerque de Oliveira, Clarice Alves Bonow, Itiberê de Oliveira Castellano Rodrigues, Amanda Xavier Geraldo

“…Introduction With the development of technology, the use of machine learning (ML), a branch of computer science that aims to transform computers into decision-making agents through algorithms, has grown exponentially. This protocol arises from the need to explore the best practices for applying ML in the communication and management of occupational risks for healthcare workers.Methods and analysis This scoping review protocol details a search to be conducted in the academic databases, Public Medical Literature Analysis and Retrieval System Online, through the Virtual Health Library: Medical Literature Analysis and Retrieval System, Latin American and Caribbean Literature in Health Sciences, West Pacific Region Index Medicus, Nursing Database and Scientific Electronic Library Online, Scopus, Web of Science and IEEE Xplore Digital Library and Excerpta Medica Database. …”
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The Impact of AI-Generated Instructional Videos on Problem-Based Learning in Science Teacher Education by Nikolaos Pellas

“…The limited impact of the preview feature highlights the need for careful design and evaluation of instructional elements, such as interactivity and adaptive learning algorithms, to fully realize their potential.…”
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Object Placement Across Robotics, Image Composition, and XR: A Mixed Reality Framework Proposal by Jalal Safari Bazargani, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi

“…This paper provides a comprehensive review of existing research on object placement, identifying key stages such as object and environment representation, placement algorithms, and evaluation metrics. A framework for object placement in MR environments is proposed, which integrates geometric and semantic representations, a human-in-the-loop approach, and real-time interaction features. …”
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Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study by Gyeongmin Kim, Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi

“…Through this method, six optimal clusters were selected with a silhouette score of 0.2831, which is a relatively higher value compared to other clustering algorithms. To clarify the characteristics of the selected groups, in-depth statistics of spatiotemporal, kinematic, and clinical features are presented in the results. …”
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SC-ResNeXt: A Regression Prediction Model for Nitrogen Content in Sugarcane Leaves by Zihao Lu, Cuimin Sun, Junyang Dou, Biao He, Muchen Zhou, Hui You

“…Compared with four classical deep learning algorithms, SC-ResNeXt exhibited superior regression prediction performance. …”
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Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU databases by Fengwei Yao, Ji Luo, Qian Zhou, Luhua Wang, Zhijun He

“…By integrating the MIMIC-IV database and machine learning algorithms, we developed an effective predictive model for HRS in liver cirrhosis patients, providing a robust tool for early clinical intervention.…”
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Palmitoylation-related gene ZDHHC22 as a potential diagnostic and immunomodulatory target in Alzheimer’s disease: insights from machine learning analyses and WGCNA by Sanying Mao, Xiyao Zhao, Lei Wang, Yilong Man, Kaiyuan Li

“…This study applied WGCNA along with three machine learning algorithms—random forest, LASSO regression, and SVM–RFE—to further select key PRGs (KPRGs). …”
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Application of Ultrasound Radiomics in Differentiating Benign from Malignant Breast Nodules in Women with Post-Silicone Breast Augmentation by Ling Hao, Yang Chen, Xuejiao Su, Buyun Ma

“…Eight machine learning algorithms were applied to build predictive models, and their performance was assessed using sensitivity, specificity, area under the ROC curve (AUC), accuracy, Brier score, and log loss. …”
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Scalable and Privacy-Preserving Inter-AS Routing Through Machine-Learning-Based Graph Pruning by Davide Andreoletti, Cristina Rottondi, Silvia Giordano, Andrea Bianco

“…Privacy-preserving shortest path algorithms are then executed on the pruned graph, at a much lower complexity. …”
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Adversarial examples defense method based on multi-dimensional feature maps knowledge distillation by Baolin QIU, Ping YI

“…The neural network approach has been commonly used in computer vision tasks.However, adversarial examples are able to make a neural network generate a false prediction.Adversarial training has been shown to be an effective approach to defend against the impact of adversarial examples.Nevertheless, it requires high computing power and long training time thus limiting its application scenarios.An adversarial examples defense method based on knowledge distillation was proposed, reusing the defense experience from the large datasets to new classification tasks.During distillation, teacher model has the same structure as student model and the feature map vector was used to transfer experience, and clean samples were used for training.Multi-dimensional feature maps were utilized to enhance the semantic information.Furthermore, an attention mechanism based on feature map was proposed, which boosted the effect of distillation by assigning weights to features according to their importance.Experiments were conducted over cifar100 and cifar10 open-source dataset.And various white-box attack algorithms such as FGSM (fast gradient sign method), PGD (project gradient descent) and C＆amp;W (Carlini-Wagner attack) were applied to test the experimental results.The accuracy of the proposed method on Cifar10 clean samples exceeds that of adversarial training and is close to the accuracy of the model trained on clean samples.Under the PGD attack of L2 distance, the efficiency of the proposed method is close to that of adversarial training, which is significantly higher than that of normal training.Moreover, the proposed method is a light-weight adversarial defense method with low learning cost.The computing power requirement is far less than that of adversarial training even if optimization schemes such as attention mechanism and multi-dimensional feature map are added.Knowledge distillation can learn the decision-making experience of normal samples and extract robust features as a neural network learning scheme.It uses a small amount of data to generate accurate and robust models, improves generalization, and reduces the cost of adversarial training.…”
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Exploring happiness factors with explainable ensemble learning in a global pandemic. by Md Amir Hamja, Mahmudul Hasan, Md Abdur Rashid, Md Tanvir Hasan Shourov

“…This paper predicts happiness scores using Machine Learning (ML), Deep Learning (DL), and ensemble ML and DL algorithms and examines the impact of individual variables on the happiness index. …”
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Person Detection for an Orthogonally Placed Monocular Camera by Pavel Skrabanek, Petr Dolezel, Zdenek Nemec, Dominik Stursa

“…As the overall price is mainly given by prices of the used sensor and processing unit, we propose the utilization of a visible spectrum camera and data processing algorithms of low time complexity to ensure a low price of the final product. …”
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Approaching maximum resolution in structured illumination microscopy via accurate noise modeling by Ayush Saurabh, Peter T. Brown, J. Shepard Bryan IV, Zachary R. Fox, Rory Kruithoff, Cristopher Thompson, Comert Kural, Douglas P. Shepherd, Steve Pressé

“…On the other hand, supervised algorithms rely on large datasets for training, and often require retraining for new sample structures. …”
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