Effective Feature Selection on Transfer Deep Learning Algorithm for Thyroid Nodules Ultrasound Detection by Ghufran Basim Alghanimi, Hadeel Aljobouri, Khaleel Akeash Alshimmari, Rasha Massoud

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Speech Emotion Recognition Model Based on Joint Modeling of Discrete and Dimensional Emotion Representation by John Lorenzo Bautista, Hyun Soon Shin

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Improving Sentiment Analysis Performance on Imbalanced Moroccan Dialect Datasets Using Resample and Feature Extraction Techniques by Zineb Nassr, Faouzia Benabbou, Nawal Sael, Touria Hamim

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Evaluation of Prediction Models for the Capping and Breaking Force of Tablets Using Machine Learning Tools in Wet Granulation Commercial-Scale Pharmaceutical Manufacturing by Sun Ho Kim, Su Hyeon Han, Dong-Wan Seo, Myung Joo Kang

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Towards AI-Assisted Mapmaking: Assessing the Capabilities of GPT-4o in Cartographic Design by Abdulkadir Memduhoğlu

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SmartSkin-XAI: An Interpretable Deep Learning Approach for Enhanced Skin Cancer Diagnosis in Smart Healthcare by Sultanul Arifeen Hamim, Mubasshar U. I. Tamim, M. F. Mridha, Mejdl Safran, Dunren Che

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Detecting and Mapping Peatlands in the Tibetan Plateau Region Using the Random Forest Algorithm and Sentinel Imagery by Zihao Pan, Hengxing Xiang, Xinying Shi, Ming Wang, Kaishan Song, Dehua Mao, Chunlin Huang

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Dataset for comparative analysis of precision metagenomics and traditional methods in urinary tract infection diagnosticsNCBI by Rob E. Carpenter, Sadia Almas, Vaibhav K. Tamrakar, Rahul Sharma

“…The dataset includes 47 urine samples, each analyzed by microbial culture, PCR, and precision metagenomics, followed by bioinformatic classification using the Explify® platform. precision metagenomics identified significantly more uropathogens (62 distinct organisms) compared to PCR (19 organisms) and microbial culture (13 organisms), with 98 % of samples testing positive for polymicrobial infections via precision metagenomics. …”
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S³DR-Det: A Rotating Target Detection Model for High Aspect Ratio Shipwreck Targets in Side-Scan Sonar Images by Quanhong Ma, Shaohua Jin, Gang Bian, Yang Cui, Guoqing Liu, Yihan Wang

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Exploring determinant factors influencing muscle quality and sarcopenia in Bilbao's older adult population through machine learning: A comprehensive analysis approach. by Naiara Virto, Danielle Marie Dequin, Xabier Río, Amaia Méndez-Zorrilla, Begoña García-Zapirain

“…Three machine learning classification algorithms classified sarcopenia and MQI in each dataset, and the performance of classification models was compared.…”
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A Method for Tomato Ripeness Recognition and Detection Based on an Improved YOLOv8 Model by Zhanshuo Yang, Yaxian Li, Qiyu Han, Haoming Wang, Chunjiang Li, Zhandong Wu

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Depression Recognition Using Daily Wearable-Derived Physiological Data by Xinyu Shui, Hao Xu, Shuping Tan, Dan Zhang

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Perceived MOOC satisfaction: A review mining approach using machine learning and fine-tuned BERTs by Xieling Chen, Haoran Xie, Di Zou, Gary Cheng, Xiaohui Tao, Fu Lee Wang

“…The study uses a MOOC corpus containing 102,184 course reviews from 401 courses across 13 disciplines. The methodology involves three approaches: (1) machine learning for automatic classification of review helpfulness, (2) BERT models for automatic classification of review topics, and (3) multiple linear regression analysis to explore the factors influencing learner satisfaction. …”
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Credit Borrower Sector of Economy and Credit Risk For Banks by Joanna Stępińska

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Automated Detection and Differentiation of Stanford Type A and Type B Aortic Dissections in CTA Scans Using Deep Learning by Hung-Hsien Liu, Chun-Bi Chang, Yi-Sa Chen, Chang-Fu Kuo, Chun-Yu Lin, Cheng-Yu Ma, Li-Jen Wang

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Spatial Differentiation in Urban Thermal Environment Pattern from the Perspective of the Local Climate Zoning System: A Case Study of Zhengzhou City, China by Jinghu Pan, Bo Yu, Yuntian Zhi

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Are the Menstrual Characteristics Similar in Adolescent and Adult Women with Cerebral Palsy? by Hanife Dogan, Duygu Turker, Ozge Coban, Merve Basol Goksuluk, Nuriye Ozengin, Necmiye Un Yildirim

“…Gross motor function levels of women with cerebral palsy were determined by gross motor function classification system expanded and revised. Menstrual-health characteristics were evaluated with a self-report questionnaire. …”
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MCBA-MVACGAN: A Novel Fault Diagnosis Method for Rotating Machinery Under Small Sample Conditions by Wenhan Huang, Xiangfeng Zhang, Hong Jiang, Zhenfa Shao, Yu Bai

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Arabic Temporal Common Sense Understanding by Reem Alqifari, Hend Al-Khalifa, Simon O’Keefe

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Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning by Hosna Tavakoli, Reza Rostami, Reza Shalbaf, Mohammad‐Reza Nazem‐Zadeh

“…Finding The classification accuracy reached as high as 79% in distinguishing schizophrenia patients from healthy in the UCLA dataset. …”
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