Anellovirus abundance as an indicator for viral metagenomic classifier utility in plasma samples by Gabriel Montenegro de Campos, Luan Gaspar Clemente, Alex Ranieri Jerônimo Lima, Eleonora Cella, Vagner Fonseca, João Paulo Bianchi Ximenez, Milton Yutaka Nishiyama, Enéas de Carvalho, Sandra Coccuzzo Sampaio, Marta Giovanetti, Maria Carolina Elias, Svetoslav Nanev Slavov

“…Interestingly, despite employing different algorithms and data types (protein-based vs. nucleotide-based), Kaiju and Kraken2 performed similarly. …”
Get full text

Advancements in biomarkers and machine learning for predicting of bronchopulmonary dysplasia and neonatal respiratory distress syndrome in preterm infants by Hanieh Talebi, Seyed Alireza Dastgheib, Maryam Vafapour, Reza Bahrami, Mohammad Golshan-Tafti, Mahsa Danaei, Sepideh Azizi, Amirhossein Shahbazi, Melina Pourkazemi, Maryam Yeganegi, Amirmasoud Shiri, Ali Masoudi, Heewa Rashnavadi, Hossein Neamatzadeh

“…For nRDS, biomarkers such as the lecithin/sphingomyelin (L/S) ratio and oxidative stress indicators have been effectively used in innovative diagnostic methods, including attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and high-content screening for ABCA3 modulation. Machine learning algorithms like Partial Least Squares Regression (PLSR) and C5.0 have shown potential in accurately identifying critical health indicators. …”
Get full text

Does mean arterial pressure augmentation improve neurological recovery of blunt spinal cord injuries: an EAST multicenter trial by Jeffry Nahmias, Ryan Peter Dumas, Brian Daley, Dalier R Mederos, Bradley M Dennis, Michael Steven Farrell, Stephanie Scott, Gregory Schaefer, Asanthi Ratnasekera, Alison Smith, Scott Armen, Joshua Hill, Carlos H Palacio, Caitlin Anne Fitzgerald, Stephanie Doris, Claudia Alvarez, John D Berne, Lindsey Perea, Aimee LaRiccia, James Bardes, Bhairav Shah, Tanisha Kashikar, Erik Teicher, Jennifer Huber, Malia Eischen, H Akin Erol, Lauren Colom, Melissa Moncrief, William DeVoe, William Brigode, Melissa Linskey Dougherty, Emily Alberto, Stephen Gadomski, Salina Wydo, Jennifer Schweinsburg, M Chance Spalding

“…Optimal hyperperfusion protocols and treatment algorithms have yet to be delineated due to a paucity of large volume prospective studies. …”
Get full text

A Hybrid Ensemble Learning Framework for Predicting Lumbar Disc Herniation Recurrence: Integrating Supervised Models, Anomaly Detection, and Threshold Optimization by Mădălina Duceac (Covrig), Călin Gheorghe Buzea, Alina Pleșea-Condratovici, Lucian Eva, Letiția Doina Duceac, Marius Gabriel Dabija, Bogdan Costăchescu, Eva Maria Elkan, Cristian Guțu, Doina Carina Voinescu

“…Predicting recurrence after lumbar disc herniation (LDH) remains clinically important but algorithmically difficult due to extreme class imbalance and low signal-to-noise ratio. …”
Get full text

THANTD: Triplet Hybrid Attention Network for Hyperspectral Target Detection by Ju Liu, Haoqian Wang, Xiangai Cheng, Zhongyang Xing, Zhongjie Xu

“…In recent years, deep learning has made significant progress in the HTD field, leading to the development of many effective algorithms. However, as a data-driven approach, deep learning methods still face challenges, such as the lack of sufficient labeled samples for training and the difficulty of capturing the diversity of spectral variations. …”
Get full text

OpenPheno: an open-access, user-friendly, and smartphone-based software platform for instant plant phenotyping by Tianqi Hu, Peng Shen, Yongshuai Zhang, Jiafei Zhang, Xin Li, Chuanzhen Xia, Ping Liu, Hao Lu, Tingting Wu, Zhiguo Han

“…In particular, OpenPheno allows developers to contribute new algorithmic tools, further expanding its capabilities to continuously facilitate the plant phenotyping community. …”
Get full text

SPA-Net: An Offset-Free Proposal Network for Individual Tree Segmentation from TLS Data by Yunjie Zhu, Zhihao Wang, Qiaolin Ye, Lifeng Pang, Qian Wang, Xiaolong Zheng, Chunhua Hu

“…Individual tree segmentation (ITS) from terrestrial laser scanning (TLS) point clouds is foundational for deriving detailed forest structural parameters, crucial for precision forestry, biomass calculation, and carbon accounting. Conventional ITS algorithms often struggle in complex forest stands due to reliance on heuristic rules and manual feature engineering. …”
Get full text

New machine-learning models outperform conventional risk assessment tools in Gastrointestinal bleeding by Eszter Boros, József Pintér, Roland Molontay, Kristóf Gergely Prószéky, Nóra Vörhendi, Orsolya Anna Simon, Brigitta Teutsch, Dániel Pálinkás, Levente Frim, Edina Tari, Endre Botond Gagyi, Imre Szabó, Roland Hágendorn, Áron Vincze, Ferenc Izbéki, Zsolt Abonyi-Tóth, Andrea Szentesi, Vivien Vass, Péter Hegyi, Bálint Erőss

“…The predictive performance of XGBoost and CatBoost machine-learning algorithms with the Glasgow-Blatchford (GBS), pre-endoscopic Rockall and ABC scores were compared. …”
Get full text

Multi-omics characterization of diabetic nephropathy in the db/db mouse model of type 2 diabetes by Liping Wang, Ran Zhou, Guanghui Li, Xiaodan Zhang, Yan Li, Yinchen Shen, Junwei Fang

“…Mechanistic pathways governing gene-metabolite-lipid interactions were inferred via random walk with restart algorithms and validated by gene set enrichment analysis (GSEA). …”
Get full text

Risk Factors and Predictive Model for Ischemic Complications in Endovascular Treatment of Intracranial Aneurysms: Insights From a Large Patient Cohort by Jianwen Jia, Zeping Jin, Mirzat Turhon, Yixin Lin, Xinjian Yang, Yang Wang, Yunpeng Liu

“…A total of five potential factors were screened using LASSO regression, XGBoost, and Randomforest algorithms: hypertension, history of alcohol consumption, multiple IAs, rupture status, and antiplatelet agent. …”
Get full text

Exploration of heterogeneity of treatment effects across exercise-based interventions for knee osteoarthritis by Paul A. Dennis, Livia Anderson, Cynthia J. Coffman, Sara Webb, Kelli D. Allen

“…Three metalearners with three machine learning algorithms each and a simple interpretable model-based regression tree were used to identify subgroups with differential treatment effects. …”
Get full text

Earth Observation Data to Support Environmental Justice: Linking Non‐Permitted Poultry Operations to Social Vulnerability Indices by Mirela G. Tulbure, Júlio Caineta, Brooke Cox, Stephen V. Stehman, Ayse Ercumen, Rebecca Witter, Ryan Emanuel, Dana E. Powell, Kemp Burdette, Sherri White‐Williamson, Shea Tuberty

“…This study highlights the critical need for comprehensive, high‐quality data on unpermitted poultry CAFOs derived using AI algorithms to fully understand their impacts on communities and accurately inform EJ evaluations.…”
Get full text

Analysis of Polarized Dust Emission Using Data from the First Flight of SPIDER by P. A. R. Ade, M. Amiri, S. J. Benton, A. S. Bergman, R. Bihary, J. J. Bock, J. R. Bond, J. A. Bonetti, S. A. Bryan, H. C. Chiang, C. R. Contaldi, O. Doré, A. J. Duivenvoorden, H. K. Eriksen, J. P. Filippini, A. A. Fraisse, K. Freese, M. Galloway, A. E. Gambrel, N. N. Gandilo, K. Ganga, S. Gourapura, R. Gualtieri, J. E. Gudmundsson, M. Halpern, J. Hartley, M. Hasselfield, G. Hilton, W. Holmes, V. V. Hristov, Z. Huang, K. D. Irwin, W. C. Jones, A. Karakci, C. L. Kuo, Z. D. Kermish, J. S.-Y. Leung, S. Li, D. S. Y. Mak, P. V. Mason, K. Megerian, L. Moncelsi, T. A. Morford, J. M. Nagy, C. B. Netterfield, M. Nolta, R. O’Brient, B. Osherson, I. L. Padilla, B. Racine, A. S. Rahlin, C. Reintsema, J. E. Ruhl, M. C. Runyan, T. M. Ruud, J. A. Shariff, E. C. Shaw, C. Shiu, J. D. Soler, X. Song, A. Trangsrud, C. Tucker, R. S. Tucker, A. D. Turner, J. F. van der List, A. C. Weber, I. K. Wehus, D. V. Wiebe, E. Y. Young, Spider Collaboration

“…Component-separation algorithms operating in both the spatial and harmonic domains are applied to probe their consistency and to quantify modeling errors associated with their assumptions. …”
Get full text

Identifying potential co-expressed genes and molecular mechanisms linking post-COVID-19 and Guillain-Barre syndrome through neutrophil extracellular trap-related genes by Jie-Hua Su, Dan-Yu Lin, Xiao-Huan Liu, Jie-Li Zhang, Zhong-Gui Li, En-Xiang Tao, Kai-Xun Huang

“…Bioinformatics functional analysis indicated that co-expressed DEGs were predominantly gathered in immune-related and inflammatory response pathways. Employing various algorithms, we identified MMP9, CAMP, and CASP1 as NETRGs, demonstrating good discriminatory capacity in COVID-19 and GBS. …”
Get full text

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir, Aiman Erbad, Bechir Hamdaoui, Samir Brahim Belhaouari, Mohsen Guizani, Thang X. Vu

“…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…”
Get full text

Construction of a circadian rhythm-related gene signature for predicting the prognosis and immune infiltration of breast cancer by Lin Ni, Lin Ni, He Li, Yanqi Cui, Wanqiu Xiong, Shuming Chen, Hancong Huang, Zhiwei Wang, Hu Zhao, Hu Zhao, Hu Zhao, Bing Wang, Bing Wang, Bing Wang

“…Three different machine learning algorithms were used to screen out the characteristic circadian genes associated with BC prognosis. …”
Get full text

Research trends and prospects in global riverine carbon fluxes: A bibliometric analysis by Wei Fang, Mohd Remy Rozainy Mohd Arif Zainol, Xianbao Zha, Pingping Luo

“…Future research should further investigate the index quantification, scaling algorithms, and modeling framework of RCFs. This study contributes to holistically understanding the evolution and prevailing trends in the field of RCFs, and better constraining the carbon budgets at the regional or global scales.…”
Get full text

Fasting Glucose of 6.1 mmol/L as a Possible Optimal Target for Type 2 Diabetic Patients with Insulin Glargine: A Randomized Clinical Trial by Lu Yuan, Fengfei Li, Yue Zhou, Rui Sun, Gu Gao, Qing Zhang, Yajuan Tang, Lu Dai, Jindan Wu, Jianhua Ma

“…To observe whether different insulin glargine titration algorithms based on fasting blood glucose (FBG) levels lead to different glycaemic variations (GVs) in type 2 diabetes (T2D) patients, a prospective, randomized, single-centre, comparative, three-arm parallel-group, open-label, treat-to-target, 24-week study was performed. …”
Get full text

GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…Implementing traditional OPF algorithms can be challenging for large-scale networks with complex topologies and constraints. …”
Get full text

Thermal ablation in the management of oligometastatic colorectal cancer by Thierry De Baere, Lambros Tselikas, Alexandre Delpla, Charles Roux, Eloi Varin, Adrian Kobe, Steven Yevich, Frederic Deschamps

“…Ablation outcomes are compared to surgical and radiation therapy literature.Results The application of thermal ablation varies widely based on tumor burden, technical expertise, and local cancer triage algorithms. Ablation can be performed in combination or in lieu of other cancer treatments. …”
Get full text