High sensitivity in spontaneous intracranial hemorrhage detection from emergency head CT scans using ensemble-learning approach by Juuso Takala, Heikki Peura, Riku Pirinen, Katri Väätäinen, Sergei Terjajev, Ziyuan Lin, Rahul Raj, Miikka Korja

“…Although the success of DL algorithms depends on multiple factors, including training data versatility and quality of annotations, using the proposed ensemble-learning approach and rule-based post-processing may help clinicians to develop highly accurate DL solutions for clinical imaging diagnostics.…”
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SynthSoM: A synthetic intelligent multi-modal sensing-communication dataset for Synesthesia of Machines (SoM) by Xiang Cheng, Ziwei Huang, Yong Yu, Lu Bai, Mingran Sun, Zengrui Han, Ruide Zhang, Sijiang Li

“…The SynthSoM dataset is open-sourced and provides consistent data for cross-comparing SoM-related algorithms.…”
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De novo KCNK4 variant caused epilepsy with febrile seizures plus, neurodevelopmental abnormalities, and hypertrichosis by Hong-Jun Yan, Wen-Hui Liu, Min-Xing Xu, Peng-Yu Wang, Yu-Jie Gu, Hua Li, Jing Guo, Sheng Luo

“…The identified variant was absent in normal populations, indicated to alter hydrogen bonds with surrounding residues by various protein modeling, predicted to be damaging for protein function by twenty algorithms, located in residues of high conservation across species, and classified as pathogenic by the ACMG guidelines. …”
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Remote Sensing Image Segmentation Using Vision Mamba and Multi-Scale Multi-Frequency Feature Fusion by Yice Cao, Chenchen Liu, Zhenhua Wu, Lei Zhang, Lixia Yang

“…Although segmentation algorithms based on convolutional neural networks (CNNs) or Transformers have achieved significant performance improvements, the trade-off between segmentation precision and computational complexity remains a key limitation for practical applications. …”
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A quality enhancement method for vehicle trajectory data using onboard images by Bozhao Li, Zhongliang Cai, Hanzhi Wei, Shiliang Su, Wenchun Cao, Yanfen Niu, Hao Wang

“…However, low-cost GPS devices often cause issues such as trajectory point deviation and key attribute missing, which reduces the potential application of trajectory data and subsequently impacts the accuracy of map updates and the quality of transportation services. Map-matching algorithms (MMs) are commonly employed to vertically match trajectory points with the road on which the vehicle is traveling, based on characteristics between the trajectory points and urban road network data. …”
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TRANSFER LEARNING MODELS COMPARISON FOR DETECTING AND DIAGNOSING SKIN CANCER by Peshraw Ahmed Abdalla, Abdalbasit Mohammed Qadir, Omed Jamal Rashid, Sarkhel H. Taher Karim, Bashdar Abdalrahman Mohammed, Karzan Jaza Ghafoor

“…To identify and diagnose skin illnesses over a range of criteria several neural network algorithms are evaluated and tested in the suggested model to see how well they perform. …”
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Developing a semi-automated technique of surface water quality analysis using GEE and machine learning: A case study for Sundarbans by Sheikh Fahim Faysal Sowrav, Sujit Kumar Debsarma, Mohan Kumar Das, Khan Mohammad Ibtehal, Mahfujur Rahman, Noshin Tabassum Hridita, Atika Afia Broty, Muhammad Sajid Anam Hoque

“…Key water quality parameters—Sea Surface Temperature (SST), Total Suspended Solids (TSS), Turbidity, Salinity, and pH—were predicted through ML algorithms and interpolated using the Empirical Bayesian Kriging (EBK) model in ArcGIS Pro. …”
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Routing Protocols Performance on 6LoWPAN IoT Networks by Pei Siang Chia, Noor Hisham Kamis, Siti Fatimah Abdul Razak, Sumendra Yogarayan, Warusia Yassin, Mohd Faizal Abdollah

“…This result is valuable to further implement these protocols in the testbed as well as provide an idea of the algorithmic enhancements.…”
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Albufera Lagoon Ecological State Study Through the Temporal Analysis Tools Developed with PerúSAT-1 Satellite by Bárbara Alvado, Luis Saldarriaga, Xavier Sòria-Perpinyà, Juan Miguel Soria, Jorge Vicent, Antonio Ruíz-Verdú, Clara García-Martínez, Eduardo Vicente, Jesus Delegido

“…The main objective of this study is to assess the potential of PerúSAT-1′s multispectral images to develop multi-parameter algorithms to evaluate the ecological state of the Albufera lagoon. …”
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Identification of cell chemistries in lithium-ion batteries: Improving the assessment for recycling and second-life by Christopher Wett, Jörg Lampe, Dominik Görick, Thomas Seeger, Bugra Turan

“…The dV/dQ characteristics are chosen as features and four machine learning algorithms are trained on different lengths of OCV curves. …”
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Pharmacologic Disruption: How Emerging Weight Loss Therapies Are Challenging Bariatric Surgery Guidelines by Safi G. Alqatari, Abrar J. Alwaheed, Manal A. Hasan, Reem J. Al Argan, Marj M. Alabdullah, Mohammed D. Al Shubbar

“…In this narrative review, we examine the evolution of surgical eligibility thresholds and critically assess the potential role of novel pharmacotherapies in redefining treatment algorithms. By comparing the efficacy, safety, metabolic benefits, and cost-effectiveness of surgery versus next-generation drugs, we explore whether a more stepwise, pharmacotherapy-first approach may now be justified, particularly in patients with BMI 30–40 kg/m². …”
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Wearable sensor-based fall detection for elderly care using ensemble machine learning techniques by Ch Gangadhar, P Pavithra Roy, R. Dinesh Kumar, Janjhyam Venkata Naga Ramesh, S. Ravikanth, N. Akhila

“…The whole assessment proved the algorithmic learning structure's efficacy. Older people's standard of existence will increase, and accidents will be avoided because of such smart tracking devices.…”
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IDENTIFICATION OF SMALL LAKES IN KAZAKHSTAN USING REMOTE SENSING DATA by Akmaral Tolepbayeva, Dinara Abiyeva, Roza Karagulova, Aigerim Tanbayeva, Zhanerke Sharapkhanova

“…However, challenges such as dense vegetation, high salinity, and the color of shallow lake bottoms led to some classification errors, highlighting the need for further refinement of automated algorithms. As a result, a list of small lakes in Kazakhstan with a surface area from 1 to 10 km2 was identified. …”
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Exploring Feature Selection with Deep Learning for Kidney Tissue Microarray Classification Using Infrared Spectral Imaging by Zachary Caterer, Jordan Langlois, Connor McKeown, Mikayla Hady, Samuel Stumo, Suman Setty, Michael Walsh, Rahul Gomes

“…In this study, we propose a deep-learning-based framework for automating classification in kidney tumor tissue microarrays (TMAs) using an IR dataset. Feature selection algorithms reduce data dimensionality, followed by a deep learning classification approach. …”
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Machine learning-based construction of Immunogenic cell death-related score for improving prognosis and personalized treatment in glioma by Guoyin Li, Yukui Zhao, Yubo He, Zhaoqiang Qian, Yiwen Liu, Xiaoyan Li, Lili Li, Zhiqiang Liu

“…CIBERSORT and ESTIMATE algorithms were employed to evaluate the infiltration of immune cells. …”
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An in silico evaluation of lorlatinib as a potential therapy for novel amino acid substitutions in the tyrosine kinase domain of the ALK protein associated with cancer by Richard Junior Zapata Dongo, Julio A. Poterico, Diletta Fontana, Luca Mologni, Carla Alvarez-Chacon, Juan Rojas-Armas, Jaeson Calla

“…Using the SIFT and Polyphen-2 algorithms, we identified 53 deleterious ALK mutations associated with different newly recognized cancer types. …”
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Integrating UAV-Based Multispectral Data and Transfer Learning for Soil Moisture Prediction in the Black Soil Region of Northeast China by Tong Zhou, Shoutian Ma, Tianyu Liu, Shuihong Yao, Shenglin Li, Yang Gao

“…This study evaluates the performance of three algorithms: Random Forest (RF), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) network. …”
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Selecting of global phenological field observations for validating coarse AVHRR-derived forest phenology products based on spatial heterogeneity and temporal consistency by Qi Shao, Chao Huang, Yuanjun Xiao, Li Liu, Weiwei Liu, Ran Huang, Chang Zhou, Wei Weng, Jingfeng Huang

“…Global phenological field observations play a crucial role in validating remote sensing products and algorithms. However, due to the spatial mismatch and scale effect between the field observations and the pixels of remote sensing phenology products, a direct comparison often leads to scale errors and increased uncertainty. …”
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A Predictive Model for Secondary Posttonsillectomy Hemorrhage in Pediatric Patients: An 8‐Year Retrospective Study by Yuting Ge, Wenchuan Chang, Lixiao Xie, Yan Gao, Yue Xu, Huie Zhu

“…Multivariate logistic regression and seven machine learning algorithms were used to construct predictive models. …”
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Authenticity Detection of Egg White Powder Using Near-Infrared Spectroscopy Based on Improved One-Dimensional Convolutional Neural Network Model by ZHU Zhihui, LI Wolin, HAN Yutong, JIN Yongtao, YE Wenjie, WANG Qiaohua, MA Meihu

“…Compared with traditional 1D-CNN network structure and other improved algorithms, the EG-1D-CNN model exhibited higher accuracy, faster detection speed, and smaller model footprint, thus making it more suitable for deployment on embedded devices. …”
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