Preparation of land subsidence susceptibility map using machine learning methods based on decision tree (case study: Isfahan–Borkhar) by Negar Ghasemi, Iman Khosravi, Ali Bahrami

“…All input datasets (as input factors for machine learning algorithms) were co-registered to match the resolution of the InSAR-derived maps (100 meters).Machine learning algorithms: Three machine learning algorithms including decision tree (DT), random forest (RF) and extreme gradient boosting (XGBoost) were tested. …”
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Flow Characteristics by Blood Speckle Imaging in Non-Stenotic Congenital Aortic Root Disease Surrounding Valve-Preserving Operations by Shihao Liu, Justin T. Tretter, Lama Dakik, Hani K. Najm, Debkalpa Goswami, Jennifer K. Ryan, Elias Sundström

“…BSI, utilizing block-matching algorithms, enabled detailed visualization and quantification of flow parameters from the echocardiographic data. …”
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Circadian rhythm abnormalities and autonomic dysfunction in patients with Chronic Fatigue Syndrome/Myalgic Encephalomyelitis. by Trinitat Cambras, Jesús Castro-Marrero, Maria Cleofé Zaragoza, Antoni Díez-Noguera, José Alegre

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Spatiotemporal evolution of interseismic coupling and stress accumulation near an asperity on a vertical strike-slip fault: Insights from three-dimensional viscoelastic numerical s... by LI Yebo, HUANG Luyuan, YAO Rui, TIAN Yiwei, YANG Shuxin

“…These models incorporate vertical strike-slip faults and use sophisticated contact algorithms to simulate the mechanical locking associated with asperities. …”
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Artificial Intelligence Driven Human Identification by Purushottam Sharma, Aazar Imran Khan, Samyak Jain, Abhishek Srivastava

“…Gait (i.e., an individual’s unique walking pattern/style) is a leading exponent when compared to first-generation biometric modalities as it is unobtrusive (i.e., it requires no contact with the individual), hence proving gait to be an optimal solution to human identification at a distance.This paper proposes an automatic identification system that analyzes gait to identify humans at a distance and predicts the strength of the match (i.e., probability of the match being positive) between two gait profiles. …”
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THE CURRENT STATE OF ARTIFICIAL INTELLIGENCE IN RADIOLOGY – A REVIEW OF THE BASIC CONCEPTS, APPLICATIONS, AND CHALLENGES by Mariana Yordanova

“…Introduction: Artificial intelligence (AI) is defined as an artificial entity capable of solving problems, learning from experience, and performing tasks such as pattern recognition and inductive reasoning. In radiology, AI aims to assist with image analysis and interpretation, potentially reducing human error and alleviating the radiological workload. …”
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Exploration of Epigenetic Mechanisms and Biomarkers Among Patients with Very-Late-Onset Schizophrenia-Like Psychosis by Gan Y, Yue W, Sun J, Yang D, Fang C, Zhou Z, Yin J, Zhou H

“…We prioritized key methylation sites through integrated analysis of methylation quantitative trait loci (meQTL), linkage disequilibrium (LD) patterns, and blood-brain methylation correlations. …”
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Voxel-based MRI intensitometry reveals extent of cerebral white matter pathology in amyotrophic lateral sclerosis. by Viktor Hartung, Tino Prell, Christian Gaser, Martin R Turner, Florian Tietz, Benjamin Ilse, Martin Bokemeyer, Otto W Witte, Julian Grosskreutz

“…VBI results correlated with disease severity (ALSFRS-R) and patterns of cerebral involvement differed between bulbar- and limb-onset. …”
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MetS: an interactive application to identify metabolites in liquid chromatography-mass spectrometry experiments with data independent acquisition by Daniel Estevan Garcia-Niño, Liliana Lopez-Kleine, Federico Roda-Fornaguera

“…The application supports filtering, correlation analysis, and similarity scoring algorithms to match DIA data to user-provided metabolite mass-to-charge ratios and fragmentation patterns. …”
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Gene expression-based modeling of overall survival in Black or African American patients with lung adenocarcinoma by Bin Zhu, Stephanie S. McHale, Michelle Van Scoyk, Gregory Riddick, Pei-Ying Wu, Chu-Fang Chou, Ching-Yi Chen, Robert A. Winn

“…Black/African American (B/AA) populations, in particular, exhibit the highest incidence and mortality rates of lung adenocarcinoma (LUAD) in the United States.MethodsThis study aims to explore gene expression patterns linked to LUAD in B/AA and case-matched white patients, with the goal of developing predictive models for prognosis. …”
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Functional Connectivity Changes in Primary Motor Cortex Subregions of Patients With Obstructive Sleep Apnea by Lifeng Li, Qimeng Shi, Bowen Fang, Yuting Liu, Xiang Liu, Yongqiang Shu, Yingke Deng, Yumeng Liu, Haijun Li, Junjie Zhou, Dechang Peng

“…Future research should explore M1 FC patterns as diagnostic markers and neuromodulation therapies.…”
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High-Speed 3D Vision Based on Structured Light Methods by Leo Miyashita, Satoshi Tabata, Masatoshi Ishikawa

“…In order to accelerate 3D vision and control the dynamic targets in real time, high-speed vision devices and high-speed image processing algorithms are essential. In this review, we revisit the basic strategy, triangulation as a suitable measurement principle for high-speed 3D vision, and introduce state-of-the-art 3D measurement methods based on high-speed vision devices and high-speed image processing utilizing structured light patterns. …”
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Towards a computer-assisted assessment of imitation in children with autism spectrum disorder based on a fine-grained analysis by Rujing Zhang, Jingying Chen, Xiaodi Liu, Yanling Gan, Guangshuai Wang

“…In this process, several quantitative indicators were applied to quantify the children’s imitation ability based on a fine-grained analysis of their visual attention and motor execution patterns. Then, three classic machine-learning algorithms were employed to explore whether the indicators could efficiently classify children with imitation difficulties. …”
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Ensemble learning techniques reveals multidimensional EEG feature alterations in pediatric schizophrenia by Ying Mao, Ying Mao, Fang Wang, Shan Wang, Zhaowei Wang, Gang Li, Xuchen Qi, Xuchen Qi, Yu Sun, Yu Sun

“…Particularly, altered FCs exhibited a fronto-increase-parieto-decrease pattern mainly in the right hemisphere along with spectral-dependent RP alterations and a universally reduced FuzEn in the pediatric SCZ group. …”
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A Hardware Architecture of a Dynamic Ranking Packet Scheduler for Programmable Network Devices by Mostafa Elbediwy, Bill Pontikakis, Jean-Pierre David, Yvon Savaria

“…The introduction of Software-Defined Networking (SDN) separated the control and data forwarding planes, but the data plane still requires a fully programmable packet scheduler that can adapt to different traffic patterns and offer high expressiveness at line rate. …”
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Data-driven intelligent productivity prediction model for horizontal fracture stimulation by Qian Li, Yiyong Sui, Mengying Luo, Bin Guan, Lu Liu, Yuan Zhao

“…Additionally, the influence patterns of proppant volume on well productivity were comprehensively analyzed to optimize reasonable proppant volumes for different wells and intervals. …”
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Nitrogen content estimation of apple trees based on simulated satellite remote sensing data by Meixuan Li, Xicun Zhu, Xicun Zhu, Xinyang Yu, Cheng Li, Dongyun Xu, Ling Wang, Dong Lv, Yuyang Ma

“…The data was resampled based on satellite sensor spectral response functions to match the band resolutions of multiple satellite sources. …”
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Overcoming therapeutic resistance in driver-negative NSCLC: Immunomodulatory mechanisms and clinical efficacy of Camrelizumab-chemotherapy combination in a real-world cohort by Yan Ge, Yang Zhao

“…Progression-free survival (PFS) was the primary endpoint, with objective response rate (ORR), resistance patterns, and treatment-related adverse events as secondary outcomes. …”
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Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction by Xin Huang, Xin Huang, Di Ouyang, Weiming Xie, Huawei Zhuang, Siyu Gao, Pan Liu, Lizhong Guo

“…This study aimed to develop and validate machine learning algorithms utilizing transcriptomic signatures to predict T1DM onset in children up to 46 months before clinical diagnosis.MethodsWe analyzed 247 peripheral blood RNA-sequencing samples from pre-diabetic children and age-matched healthy controls. …”
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Potential applications of gene expression profiles obtained from circulating extracellular vesicles in breast cancer by Aritra Gupta, Siddharth Bhardwaj, Sayan Ghorai, Rosina Ahmed, Sanjit Agarwal, Geetashree Mukherjee, Kartiki V. Desai

“…EVs from metastatic samples had higher variability in gene expression patterns whereas those from non-metastatic samples showed a better correlation. …”
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