Artificial Intelligence in Diagnosis and Management of Nail Disorders: A Narrative Review by Vishal Gaurav, Chander Grover, Mehul Tyagi, Suman Saurabh

“…AI algorithms, particularly deep convolutional neural networks (CNNs), have demonstrated high sensitivity and specificity in interpreting nail images, aiding differential diagnosis as well as enhancing the efficiency of diagnostic processes in a busy clinical setting. …”
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Optimising after-hours workflow of computed tomography orders in the emergency department by Joseph Choi, Rajesh Bhayana, Chenhan D Wang, Ravi J Menezes, Eric S Bartlett

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Hybrid pre trained model based feature extraction for enhanced indoor scene classification in federated learning environments by Monica Dutta, Deepali Gupta, Vikas Khullar, Sapna Juneja, Roobaea Alroobaea, Pooja Sapra

“…Deep Learning (DL) models, especially Convolutional Neural Networks (CNNs), have improved classification accuracy significantly by extracting the image features. …”
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Selecting a Superior Landing Area in the Region Far From Procellarum KREEP Terrane by Wenqing Chang, Zhiguo Meng, Xuegang Dong, Meng Zou, Xiaoping Zhang, Yuanzhi Zhang

“…Mare Crisium, located in the area, has been identified as an essential landing option for the Lunar Geophysical Network (LGN) mission. Utilizing high-resolution images, topographic data, surface compositions, and Chang'e-2 microwave radiometer (MRM) data, a systematic analysis and comparison have been done between Maria Crisium and Smythii in terms of geomorphological feature, regolith properties, lunar crust and mantle properties, and microwave thermal emission characteristics. …”
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Improved Alzheimer Disease Diagnosis With a Machine Learning Approach and Neuroimaging: Case Study Development by Lilia Lazli

“…These features are fed into feedforward neural networks (FFNNs) and SVM-based ML classifiers. Furthermore, we applied the vision transformer (ViT)–based ANNs in conjunction with data augmentation to distinguish patients with AD from healthy controls. …”
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Enhancing Software Defect Prediction Using Ensemble Techniques and Diverse Machine Learning Paradigms by Ayesha Siddika, Momotaz Begum, Fahmid Al Farid, Jia Uddin, Hezerul Abdul Karim

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Accuracy is not enough: a heterogeneous ensemble model versus FGSM attack by Reham A. Elsheikh, M. A. Mohamed, Ahmed Mohamed Abou-Taleb, Mohamed Maher Ata

“…The results from the experiments show that the advised HEM_Net model accuracy declined drastically by 59.72% for CK + data, 42.53% for RafD images, and 48.49% for the Jaffee dataset when the perturbation increased from A to E (attack levels). …”
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A Framework for Breast Cancer Classification with Deep Features and Modified Grey Wolf Optimization by Fathimathul Rajeena P.P, Sara Tehsin

“…Pre-trained convolutional neural network models trained on generic datasets tend to extract irrelevant features when applied to domain-specific classification tasks, highlighting the need for a feature selection mechanism to transform high-dimensional data into a more discriminative feature space. …”
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Regional Peculiarities of the Development of Russian Siberian Folklore Studies in the Early 20th Century (Pre-October Period) by Natalya A. Ursegova

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The role of quantitative EEG biomarkers in Alzheimer’s disease and mild cognitive impairment: applications and insights by Yue Yuan, Yang Zhao

“…We highlight the application of qEEG biomarkers, including power spectrum analysis (oscillatory activity within frequency bands), functional connectivity (coherent neural couplings) and effective connectivity (directional neural interactions), microstates (brief, stable states of the brain network), and non-linear analyses (e.g., entropy and EEG network analysis). …”
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Impaired Brain Information Transmission Efficiency and Flexibility in Parkinson’s Disease and Rapid Eye Movement Sleep Behavior Disorder: Evidence from Functional Connectivity and... by Jing Wei, Jiaqi Lyu, Jie Xiang, Yan Niu, Lan Yang, Chanjuan Fan, Dandan Li, Yanli Yang

“…To prove our hypothesis, we performed functional connectivity (FC) and functional dynamics analysis of three aspects—based on the whole brain, within the resting-state network (RSN), and the interaction between RSNs—using normal control (NC) (n = 21), RBD (n = 24), and PD (n = 45) resting-state functional magnetic resonance imaging (rs-fMRI) data sets. …”
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388 Subtyping social determinants of health in cancer: Implications for health equity policies by Suresh Bhavnani, Suresh K. Bhavnani, Rodney Hunter, Susanne Schmidt, Brian Downer, Jeremy Warner

“…Results/Anticipated Results: As shown in Fig. 1A (http://www.skbhavnani.com/DIVA/Images/Cancer-SDoH.jpg), the analysis (n = 3361, d = 18) identified 4 biclusters with significant biclusteredness (Q = 0.13, random-Q = 0.11, z = 9.94, P Discussion/Significance of Impact: Currently, many health equity policies allocate resources based on sociodemographic factors like race and income to address disparities. …”
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Accelerating the k-Means++ Algorithm by Using Geometric Information by Guillem Rodriguez Corominas, Maria J. Blesa, Christian Blum

“…Real-world use cases include social network analysis, medical imaging, market segmentation, and anomaly detection, to name a few. …”
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Identification Method of Dynamic Propagation Process of Rock Fracture Based on Ground Penetrating Radar by CHEN Jun, ZHANG Bo, ZHUANG Xingyue, SONG Zhishu, ZHENG Jun

“…Additionally, the application of deep learning algorithms, such as convolutional neural networks and Transformers, can automate the process of GPR image analysis, reducing human bias and improving the efficiency of data interpretation.ConclusionsThe findings of this study demonstrate the significant potential of GPR technology for dynamic monitoring of rock mass fractures. …”
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Framework for timely perception of spatiotemporal crowd congestion risk in public spaces based on video pedestrian tracking and geographic mapping by Shaojun Liu, Ling Zhang, Junlian Ge, Weitao Li, Yi Long

“…The popularity of sensor networks and the rapid development of computer vision technology have made it possible to collect and perceive spatial and temporal information ubiquitously, creating valuable opportunities for the rapid analysis of geographic phenomena and timely detection of potential problems. …”
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Reanalysis of the longest mass balance series in Himalaya using a nonlinear model: Chhota Shigri Glacier (India) by M. F. Azam, C. Vincent, S. Srivastava, S. Srivastava, E. Berthier, P. Wagnon, H. Kaushik, Md. A. Hussain, M. K. Munda, A. Mandal, A. Ramanathan

“…</mo></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="32pt" height="8pt" class="svg-formula" dspmath="mathimg" md5hash="25fef67db633bdf487823a453c1c7b7f"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-18-5653-2024-ie00004.svg" width="32pt" height="8pt" src="tc-18-5653-2024-ie00004.png"/></svg:svg></span></span> Our analysis suggests that the nonlinear model can also be used to complete the MB series if for some years the field observations are poor or unavailable. …”
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Clear Cell Acanthoma/Pseudolymphoma: Clinical­ Dermatoscopic and Histological Correlation by Shulaia T., Kiladze N., Miriamidze A.

“…For the immersion dermatoscopy ultrasound gel was used. All obtained images were estimated in accordance with the algorithm of G. …”
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Contemporary digital sociology in search of meaning-making models: the proper and the actual. Review on articles from the research handbook of digital sociology edited by J. Skopek... by E. V. Andrianova, V. A. Davydenko, A. I. Rozmanov

“…The first part of this review presents the key ideas of 15 chapters, focusing on the foundational components of social  theory and their connections to the internet in daily life, digital  technologies for surveys and data processing, the significance  of mobile devices, big data, machine learning, agent-based  models of social phenomena, inclusive digital focus groups, social networking sites in professional contexts, online dating, partner selection based on digital information, the use of digital approaches in online markets, the application of YouTube in social sciences, and automated image analysis. …”
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Transition and dynamic reconfiguration in late-life depression based on hidden Markov model by Hairong Xiao, Caili Kang, Wei Zhao, Shuixia Guo

“…Here, we employed a hidden Markov model to analyze resting-state functional magnetic resonance imaging data from 154 patients with late-life depression and 147 healthy controls. …”
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Rehabilitation training robot using mirror therapy for the upper and lower limb after stroke: a prospective cohort study by Xixi Wu, Xu Qiao, Yudi Xie, Qingyan Yang, Wenting An, Lingfeng Xia, Jiatao Li, Xiao Lu

“…Functional magnetic resonance imaging (fMRI) was conducted on 30 patients to assess changes in the brain network. …”
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