A Large-Scale Inter-Comparison and Evaluation of Spatial Feature Engineering Strategies for Forest Aboveground Biomass Estimation Using Landsat Satellite Imagery by John B. Kilbride, Robert E. Kennedy

“…Statistical features that characterize image texture have been proposed as a means to alleviate spectral saturation. However, apart from Gray Level Co-occurrence Matrix (GLCM) statistics, many spatial feature engineering techniques (e.g., morphological operations or edge detectors) have not been evaluated in the context of forest AGB estimation. …”
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A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

“…We also evaluated the performance of various algorithms (e.g., Random Forest (RF), Convolutional Neural Networks (CNN), Graph Neural Networks (GNN), and Multi-Layer Perceptron (MLP)) across these models. …”
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Development of machine learning predictive models and risk scoring system for survival in breast cancer patients with type II diabetes: a retrospective cohort study by Claire Chenwen Zhong, Junjie Huang, Zhaojun Li, Yu Jiang, Zehuan Yang, Ziwei Huang, Qi Dou, Yu Li, Martin C.S. Wong

“…Findings: This retrospective cohort study included 8,255 breast cancer patients with T2DM. The mean survival time was 97.83 months (SD: 70.39), with 99.21% female and 16.00% deceased. …”
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Machine learning models for prediction of lymph node metastasis in patients with gastric cancer: a Chinese single-centre study with external validation in an Asian American populat... by Qian Li, Yuan Tian, Wei Peng, Shangcheng Yan, Weiran Yang, Zhuan Du, Ming Cheng, Renwei Chen, Qiankun Shao, Mengchao Sheng, Yongyou Wu

“…Objective To develop and validate machine learning (ML)-based models to predict lymph node metastasis (LNM) in patients with gastric cancer (GC).Design Retrospective cohort study.Setting Second Affiliated Hospital of Soochow University.Participants A total of 500 inpatients from the Second Affiliated Hospital of Soochow University, collected retrospectively between 1 April 2018 and 31 March 2023, were used as the training set, while 824 Asian patients from the Surveillance, Epidemiology and End Results database comprised the external validation set.Main outcome measures Prediction models were developed using multiple ML algorithms, including logistic regression, support vector machine, k-nearest neighbours, naive Bayes, decision tree (DT), gradient boosting DT, random forest and artificial neural network (ANN). …”
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Multi-scenario Dynamic Simulation and Optimization of Urban Ventilation Environment: A Case Study of Taiyuan Metropolitan Area by Junda HUANG, Yuncai WANG

“…Then, a prediction model is constructed based on the random forest algorithm. The land use types and ventilation environment of multiple scenarios in 2010 and 2020 are input into the validated prediction model to simulate changes in the future ventilation environment. …”
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Clinical and Imaging Features of Sporadic and Genetic Frontotemporal Lobar Degeneration TDP‐43 A and B by Sean Coulborn, Rhiana Schafer, Ashlin R. K. Roy, Andrzej Sokolowski, Noah G. Cryns, Dana Leichter, Argentina Lario Lago, Eliana Marisa Ramos, Yann Cobigo, Salvatore Spina, Lea T. Grinberg, Daniel H. Geschwind, Maria L. Gorno‐Tempini, Joel H. Kramer, Howard J. Rosen, Bruce L. Miller, William W. Seeley, David C. Perry

“…Methods We generated individual atrophy maps and extracted mean atrophy scores for regions of interest—frontotemporal, occipitoparietal, thalamus, and cerebellum—in 54 patients with FTLD‐TDP types A or B. …”
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A panting behavior-driven assessment framework for summer ventilation quality optimization in layer houses by Zixuan Zhou, Lihua Li, Hao Xue, Yuchen Jia, Yao Yu, Zongkui Xie, Yuhan Gu

“…The YOLOv10-BCE panting behavior detection model was developed by embedding the BiFormer module into the backbone network to enhance multi-dimensional feature extraction, compressing neck structure parameters using the C3Ghost module, and integrating Efficient Intersection over Union (EIOU) loss to improve detection accuracy and convergence speed. K-means clustering and linear regression algorithms were employed to establish a quantitative correlation curve between ventilation quality and panting behavior, forming a Normal-Alert-Danger ventilation quality (VQ) classification standard. …”
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Enhancing Detection of Multi-Frequency-Modulated SSVEP Using Phase Difference Constrained Canonical Correlation Analysis by Chi Man Wong, Ze Wang, Boyu Wang, Agostinho Rosa, Tzyy-Ping Jung, Feng Wan

“…However, the existing calibration-free recognition algorithms based on the traditional canonical correlation analysis (CCA) cannot provide the merited performance. …”
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Inertial-Based Dual-Task Gait Normalcy Index at Turns: A Potential Novel Gait Biomarker for Early-Stage Parkinson’s Disease by Lin Meng, Xiaofei Zhang, Yu Shi, Xinge Li, Jun Pang, Lei Chen, Xiaodong Zhu, Rui Xu, Dong Ming

“…As one of the main motor indicators of Parkinson’s disease (PD), postural instability and gait disorder (PIGD) might manifest in various but subtle symptoms at early stage resulting in relatively high misdiagnosis rate. …”
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Detecting Post-Midnight Plasma Depletions Through Plasma Density and Electric Field Measurements in the Low-Latitude Ionosphere by Giulia D’Angelo, Emanuele Papini, Alessio Pignalberi, Dario Recchiuti, Piero Diego

“…To test the robustness and reliability of our algorithms, we also applied them to well-established Swarm B satellite observations. …”
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Enhanced MCDM Based on the TOPSIS Technique and Aggregation Operators Under the Bipolar pqr-Spherical Fuzzy Environment: An Application in Firm Supplier Selection by Zanyar A. Ameen, Hariwan Fadhil M. Salih, Amlak I. Alajlan, Ramadhan A. Mohammed, Baravan A. Asaad

“…Moreover, a numerical example is provided in order to ensure that the presented model is applicable. By using the two algorithms, a comparative analysis of the proposed method with other existing ones is given in order to verify the feasibility of the suggested decision-making procedure.…”
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Development and validation of a population pharmacokinetic model to guide perioperative tacrolimus dosing after lung transplantation by Todd A. Miano, PharmD, PhD, Athena F. Zuppa, MD, MSCE, Rui Feng, PhD, Stephen Griffiths, BS, Laurel Kalman, BA, Michelle Oyster, MS, Edward Cantu, MD, MSCE, Wei Yang, PhD, Joshua M. Diamond, MD, MSCE, Jason D. Christie, MD, MSCE, Marc H. Scheetz, PharmD, MSC, Michael G.S. Shashaty, MD, MSCE

“…Population PK models that include lung-transplant–specific covariates may enable precision dosing algorithms that account for this highly dynamic clearance. …”
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The Association of Aortic Stenosis Severity and Symptom Status With Morbidity and Mortality by Matthew D. Solomon, MD, PhD, Alan S. Go, MD, Thomas Leong, MPH, Elisha Garcia, BS, Kathy Le, MPH, Femi Philip, MD, Edward McNulty, MD, Jacob Mishell, MD, Andrew N. Rassi, MD, David C. Lange, MD, Catherine Lee, PhD, Anthony DeMaria, MD, Rick Nishimura, MD, Andrew P. Ambrosy, MD

“…Symptomatic patients were older (mean age 78 vs 75 years; P < 0.01), more often female (51% vs 47%; P < 0.01), and had greater comorbidity burden. …”
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D-pinitol modulates the anti-emetic effects of aprepitant, domperidone, and ondansetron in chicks by Md. Elit Rahman, Md. Anisur Rahman, Salehin Sheikh, Md. Jannatul Islam Polash, Sozoni Khatun, Mst. Sonia Akter Bristi, Md. Showkoth Akbor, Mst. Farjanamul Haque, Mehedi Hasan Bappi, Tohidul Islam Tanim, Siddique Akber Ansari, Irfan Aamer Ansari, Elaine Cristina Pereira Lucetti, Carolina Bandeira Domiciano, Henrique D.M. Coutinho, Muhammad Torequl Islam

“…Additionally, A variety of computational algorithms were used to visualise ligand–receptor interactions and quantify the binding affinities of DPL and other ligands towards the dopamine receptors (D2 and D3), muscarinic acetylcholine receptors (M1–M5), and serotonin receptor (5HT3). …”
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Prediction of stable structure and unique charge transfer in Li–Pt intermetallic compounds under pressure by Wenlin Xu, Dengjie Yan, Liguo Zhu, Yifei Wang, Lingxin Kong, Bin Yang, Baoqiang Xu

“…This work demonstrates that tuning the pressure and stoichiometry is an effective means of forming novel, stable intermetallic compounds.…”
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Prediction of additional hospital days in patients undergoing cervical spine surgery with machine learning methods by Bin Zhang, Shengsheng Huang, Chenxing Zhou, Jichong Zhu, Tianyou Chen, Sitan Feng, Chengqian Huang, Zequn Wang, Shaofeng Wu, Chong Liu, Xinli Zhan

“…Background Machine learning (ML), a subset of artificial intelligence (AI), uses algorithms to analyze data and predict outcomes without extensive human intervention. …”
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Challenges and inequalities in the management of financing the tasks of local government units: a critical analysis by Arkadiusz Ciach

“…Do the currently used algorithms for the distribution of subsidies reflect the real needs of local government units, and, as a result, there is an optimal allocation of public funds? …”
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Optimal vaccination model of airborne infection under variable humidity and demographic heterogeneity for hybrid fractional operator technique by Saima Rashid, Ilyas Ali, Nida Fatima, Tehreem Fatima, Fekadu Tesgera Agam, Sayed K. Elagan

“…This study proposes the dynamics of the influenza epidemic in the province of Madrid, Spain, with an emphasis on the effects of control employing actual data. The main challenge is accurately estimating the virus’s rate of transmission and assessing the effectiveness of vaccination campaigns. …”
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Diagnosis methods for pancreatic cancer with the technique of deep learning: a review and a meta-analysis by Yuanbo Bi, Dongrui Li, Ruochen Pang, Chengxv Du, Da Li, Xiaoyv Zhao, Haitao Lv

“…Inclusion criteria were studies involving PDAC patients, using deep learning algorithms for diagnosis evaluation, using histopathological results as the reference standard, and having sufficient data. …”
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Control Tolerante a Fallas Activo: Estimación y acomodación de fallas en sensores aplicado al modelo LPV de una bicicleta sin conductor by J.A. Brizuela-Mendoza, C.M. Astorga-Zaragoza, A. Zavala-Río, F. Canales-Abarca

“…Within the Active Fault Tolerant Control, the detection and diagnostic system is based on the estimations computed by a fault observer, used to determine a fault occurrence. The proposed algorithms, considered as the main contributions in this work, achieves noise-free estimations for the faults and state, in order to compute the fault indicator and control law, respectively. …”
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