SSMM: Semi-supervised manifold method with spatial-spectral self-training and regularized metric constraints for hyperspectral image dimensionality reduction by Bei Zhu, Yao Jin, Xuehua Guan, Yanni Dong

“…SSMM conducts various forms of experiments on the Houston 2013, Indian Pines, and Washington DC datasets. In the dimensionality reduction experiments, the overall accuracy of SSMM in any dimension is higher than that of other algorithms. …”
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The Golden Afromontane ecosystems at cross-road: Wetland-based upstream-downstream linkage in Genale Dawa River Basin by Habtamu Temesgen, Haile Ketema, Gezahegn Kebede, Fikadu Woldemariyam, Gebremedihin Tesfaye

“…Landsat images between 2005 and 2020, along with documents review, were utilized to generate datasets. A stakeholders’ consultation forum and expert judgment were employed to understand the historical ecology of WESs in the GDRB. …”
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Lossless and reference-free compression of FASTQ/A files using GeneSqueeze by Foad Nazari, Sneh Patel, Melissa LaRocca, Alina Sansevich, Ryan Czarny, Giana Schena, Emma K. Murray

“…As such, GeneSqueeze has the potential to significantly reduce the storage and transmission costs associated with large omics datasets without sacrificing data integrity.…”
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A revisit of the semi-geostrophic eddy east of the Sri Lanka dome with anisotropy insight by Zhou Le, M. V. Subrahmanyam, Pemmani Venkata Subba Raju, Gayan Pathirana, Dongxiao Wang, Dongxiao Wang, Wei Song

“…Acknowledging the importance of this phenomenon, this study revisits the SG eddy using satellite altimetry data, reanalysis datasets and in-situ observations from the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) project. …”
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NavBLIP: a visual-language model for enhancing unmanned aerial vehicles navigation and object detection by Ye Li, Li Yang, Meifang Yang, Fei Yan, Tonghua Liu, Chensi Guo, Rufeng Chen

“…Furthermore, NavBLIP employs a multimodal control strategy that dynamically selects context-specific features to optimize real-time performance, ensuring efficiency in high-stakes operations.Results and discussionExtensive experiments on benchmark datasets such as RefCOCO, CC12M, and Openlmages reveal that NavBLIP outperforms existing state-of-the-art models in terms of accuracy, recall, and computational efficiency. …”
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Use of virtual care near the end of life before and during the COVID-19 pandemic: A population-based cohort study. by Kieran L Quinn, Thérèse A Stukel, Allan Detsky, Hannah Chung, Mohammed Rashidul Anwar, Sacha Bhatia, James Downar, Vivian Hung, Sarina Isenberg, Allison Kurahashi, Douglas S Lee, Nathan Stall, Peter Tanuseputro, Chaim M Bell

“…<h4>Methods</h4>We used linked clinical and administrative datasets to study use of virtual care in the last three months of life among 411,564 adults who died between January 25, 2018, and November 30, 2022. …”
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Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring by Fang Li, Shengguo Wang, Zhi Gao, Maofeng Qing, Shan Pan, Yingying Liu, Chengchen Hu

“…Future research should focus on refining AI algorithms with diverse datasets, integrating emerging technologies, and fostering interdisciplinary collaboration to address these challenges and realize AI’s transformative potential in sepsis care.…”
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Investigating the correlation of hip circumference to cardiovascular disease and type‐2 diabetes using Mendelian randomization by Hongtao Liu, Zhaoyu Li, Su Yan, Shaopeng Ming

“…Main Outcome Measures Publicly available summary statistics datasets from GWAS meta‐analyses were used, with HC and HC adjusted for body mass index (BMI) as exposures. …”
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Identification of GPD1L as a Potential Prognosis Biomarker and Associated with Immune Infiltrates in Lung Adenocarcinoma by Zhengyang Fan, Song Wu, Hongyang Sang, Qianping Li, Shaofei Cheng, Hongling Zhu

“…In this study, following an examination of the TGCA datasets, we found that GPD1L displayed a dysregulated state in a wide variety of cancers; this led us to believe that GPD1L is an essential regulator in the progression of malignancies. …”
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SMR-guided molecular subtyping and machine learning model reveals novel prognostic biomarkers and therapeutic targets in non-small cell lung adenocarcinoma by Baozhen Wang, Yichen Yin, Anqi Wang, Weidi Liu, Jing Chen, Tao Li

“…In this study, we integrated data from multiple public datasets, including TCGA, GSE31210, and GSE13213, encompassing a total of 867 tumor samples. …”
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Seasonal Land Use and Land Cover Mapping in South American Agricultural Watersheds Using Multisource Remote Sensing: The Case of Cuenca Laguna Merín, Uruguay by Giancarlo Alciaturi, Shimon Wdowinski, María del Pilar García-Rodríguez, Virginia Fernández

“…The materials include Sentinel-2, Sentinel-1 and Shuttle Radar Topography Mission imagery, Google Earth Engine, training and validation datasets and quoted classifiers. The methods involve creating a multisource database, conducting feature importance analysis, developing models, supervised classification and performing accuracy assessments. …”
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High Expression of Ten Eleven Translocation 1 Is Associated with Poor Prognosis in Hepatocellular Carcinoma by Haopeng Wen, Tengfei Ji, Liteng Lin, Nan Cheng, Kangshun Zhu, Liangqi Cao

“…Materials and Methods. Four independent datasets with gene expression data and clinical data of HCC samples were downloaded from public databases. …”
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Factors associated with, and variations in, COVID-19 hospital death rates in England’s first two waves: observational study by Alex Bottle, Paul Aylin, Stephen Brett, Puji Faitna

“…To quantify the correlation between hospitals’ first and second wave death rates.Design Observational study using administrative data.Setting Acute non-specialist hospitals in England.Participants All patients admitted with a primary diagnosis of COVID-19.Primary and secondary outcomes In-hospital death.Results Hospital Episode Statistics (HES) data were extracted for all acute hospitals in England for COVID-19 admissions from March 2020 to March 2021. …”
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A foundation systematic review of natural language processing applied to gastroenterology & hepatology by Matthew Stammers, Balasubramanian Ramgopal, Abigail Owusu Nimako, Anand Vyas, Reza Nouraei, Cheryl Metcalf, James Batchelor, Jonathan Shepherd, Markus Gwiggner

“…Therefore, greater clinical engagement, collaboration, and open sharing of appropriate datasets and code are needed.…”
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Enhance health evidence quality in classification tasks: A triangulation approach utilizing case-based reasoning and process features by Ruihua Guo, Ross Smith, Qifan Chen, Angus Ritchie, Simon Poon

“…However, more scalable QCA methods are needed for larger datasets. Developing health process feature engineering for broader applications can be a future direction.…”
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Identification and Validation of the Pyroptosis-Related Hub Gene Signature and the Associated Regulation Axis in Diabetic Keratopathy by Yi Cui, Li Wang, Wentao Liang, Li Huang, Shuting Zhuang, Hong Shi, Nuo Xu, Jianzhang Hu

“…Intersection of DEGs and pyroptosis-related datasets showed 33 differentially expressed pyroptosis-related genes (DEPRGs) associated with pathways such as IL-17, NOD-like receptor, TNF, and Toll-like receptor signaling. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…As environmental sciences increasingly rely on complex datasets, machine learning (ML) has become crucial for identifying patterns and relationships. …”
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DGL-STFA: Predicting lithium-ion battery health with dynamic graph learning and spatial–temporal fusion attention by Zheng Chen, Quan Qian

“…Extensive experiments were conducted on the NASA and CALCE battery datasets, comparing this framework with traditional time-series prediction methods and other graph-based prediction methods. …”
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EPRNG: Effective Pseudo-Random Number Generator on the Internet of Vehicles Using Deep Convolution Generative Adversarial Network by Chenyang Fei, Xiaomei Zhang, Dayu Wang, Haomin Hu, Rong Huang, Zejie Wang

“…In this paper, we propose an Effective Pseudo-Random Number Generator (EPRNG) which exploits a deep convolution generative adversarial network (DCGAN)-based approach using our processed vehicle datasets and entropy-driven stopping method-based training processes for the generation of pseudo-random numbers. …”
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Impacts of Strategic Mobility Restrictions Policies during 2020 COVID-19 Outbreak on Brazil’s Regional Air Quality by Anderson P. Rudke, Daniela S. de Almeida, Ronaldo A. Alves, Alexandra Beal, Leila D. Martins, Jorge A. Martins, Ricardo Hallak, Taciana T. de Almeida Albuquerque

“…Therefore, air quality (CO, NO2, PM10, PM2.5, and O3) and urban mobility datasets available in five populous Brazilian states (São Paulo, Rio de Janeiro, Espírito Santo, Paraná, and Rio Grande do Sul) were analyzed. …”
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