A Spatiotemporal Feature Extraction Technique Using Superlet-CNN Fusion for Improved Motor Imagery Classification by Neha Sharma, Manoj Sharma, Amit Singhal, Nuzhat Fatema, Vinay Kumar Jadoun, Hasmat Malik, Asyraf Afthanorhan

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Enhanced Conformer-Based Speech Recognition via Model Fusion and Adaptive Decoding with Dynamic Rescoring by Junhao Geng, Dongyao Jia, Zihao He, Nengkai Wu, Ziqi Li

“…Second, for the decoding phase, we design a dynamic adaptive decoding method that combines traditional decoding algorithms such as connectionist temporal classification and attention-based models. …”
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Assessing the Severity of ODT and Factors Determinants of Late Arrival in Young Patients with Acute Ischemic Stroke by Zhu L, Li Y, Zhao Q, Li C, Wu Z, Jiang Y

“…Pre-hospital delays are prevalent, particularly in China, yet targeted research on the youth population remains scarce.Methods: In this retrospective cohort study, data from AIS patients aged 18– 50 admitted to Longhua District People’s Hospital, Shenzhen from December 2021 to December 2023 were analyzed using XGBoost and Random Forest machine learning algorithms, coupled with SHAP visualization, to identify factors contributing to pre-hospital delays.Results: Among 1954 AIS patients, 528 young patients were analyzed. …”
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Clinical Guidelines of the Russian Society for the Study of the Liver, Russian Gastroenterological Association, Russian Society for the Prevention of Non-Communicable Diseases, Rus... by V. T. Ivashkin, O. M. Drapkina, M. V. Maevskaya, K. L. Raikhelson, S. V. Okovityi, M. S. Zharkova, V. R. Grechishnikova, D. I. Abdulganieva, S. A. Alekseenko, M. D. Ardatskaya, I. G. Bakulin, N. V. Bakulina, P. O. Bogomolov, V. V. Breder, E. V. Vinnitskaya, N. I. Geyvandova, E. V. Golovanova, V. B. Grinevich, V. L. Doshchitsin, E. N. Dudinskaya, E. V. Ershova, K. B. Kodzoeva, I. V. Kozlova, K. A. Komshilova, Yu. V. Konev, N. V. Korochanskaya, Yu. V. Kotovskaya, Yu. A. Kravchuk, I. D. Loranskaya, I. V. Maev, A. I. Martynov, S. N. Mekhtiev, E. E. Mishina, M. Yu. Nadinskaia, I. G. Nikitin, M. F. Osipenko, O. D. Ostroumova, Ch. S. Pavlov, N. V. Pogosova, V. G. Radchenko, G. E. Roytberg, R. G. Saifutdinov, A. A. Samsonov, P. V. Seliverstov, S. I. Sitkin, L. V. Tarasova, A. I. Tarzimanova, O. N. Tkacheva, E. I. Tkachenko, E. A. Troshina, S. V. Turkina, Yu. P. Uspenskiy, Yu. A. Fominykh, O. V. Khlynova, Yu. V. Tsyganova, M. Sh. Shamkhalova, O. O. Sharkhun, M. V. Shestakova

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A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults by Daisu Abe, Motoki Inaji, Takeshi Hase, Eiichi Suehiro, Naoto Shiomi, Hiroshi Yatsushige, Shin Hirota, Shu Hasegawa, Hiroshi Karibe, Akihiro Miyata, Kenya Kawakita, Kohei Haji, Hideo Aihara, Shoji Yokobori, Takeshi Maeda, Takahiro Onuki, Kotaro Oshio, Nobukazu Komoribayashi, Michiyasu Suzuki, Taketoshi Maehara

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A multimodal approach for enhanced disease management in cauliflower crops: integration of spectral sensors, machine learning models and targeted spraying technology by Rohit ANAND, Roaf Ahmad PARRAY, Indra MANI, Tapan Kumar KHURA, Harilal KUSHWAHA, Brij Bihari SHARMA, Susheel SARKAR, Samarth GODARA, Shideh MOJERLOU, Hasan MIRZAKHANINAFCHI

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Enhancing Pollen Prediction in Beijing, a Chinese Megacity: Leveraging Ensemble Learning Models for Greater Accuracy by Wenxi Ruan, Ziming Li, Zhaobin Sun, Xingqin An, Yuxin Zhao, Shuwen Zhang, Yinglin Liang, Yaqin Bu, Jingyi Xin, Xiaoyi Hang

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Optimal Parameter Extraction of PEM Fuel Cell Using a Hybrid Weighted Mean of Vectors and Nelder-Mead Simplex Method by Rahul Khajuria, Mahipal Bukya, Ravita Lamba, Rajesh Kumar

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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

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Clustering Electrophysiological Predisposition to Binge Drinking: An Unsupervised Machine Learning Analysis by Marcos Uceta, Alberto del Cerro‐León, Danylyna Shpakivska‐Bilán, Luis M. García‐Moreno, Fernando Maestú, Luis Fernando Antón‐Toro

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Many-Objective Truss Structural Optimization Considering Dynamic and Stability Behaviors by João Marcos P. Vieira, José Pedro G. Carvalho, Dênis E. C. Vargas, Érica C. R. Carvalho, Patrícia H. Hallak, Afonso C. C. Lemonge

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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…A thematic analysis was employed to categorize and synthesize the data. Results Nineteen studies were included. The primary AI approaches were machine learning, neural networks, and chatbot development. …”
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Optimized Identification of Sentence-Level Multiclass Events on Urdu-Language-Text Using Machine Learning Techniques by Somia Ali, Uzma Jamil, Muhammad Younas, Bushra Zafar, Muhammad Kashif Hanif

“…However, for low-resource languages like Urdu, there is a scarcity of well-structured data for specific tasks such as event classification. …”
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Network pharmacology and AI in cancer research uncovering biomarkers and therapeutic targets for RALGDS mutations by S. Mohammed Zaidh, Hariharan Thirumalai Vengateswaran, Mohammad Habeeb, Kiran Balasaheb Aher, Girija Balasaheb Bhavar, N. Irfan, K N V Chenchu Lakshmi

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Exploring suicidal thoughts among prospective university students: a study with applications of machine learning and GIS techniques by Mohammed A. Mamun, Firoj Al-Mamun, Md Emran Hasan, Nitai Roy, Moneerah Mohammad ALmerab, David Gozal, Md. Shakhaoat Hossain

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Spatiotemporal estimation of ambient forest phytoncides: Unveiling patterns through geospatial-based machine learning approach by Aji Kusumaning Asri, Hao-Ting Chang, Chia-Pin Yu, Wan-Yu Liu, Yinq-Rong Chern, Rui-Hao Xie, Shih-Chun Candice Lung, Kai Hsien Chi, Yu-Cheng Chen, Sen-Sung Cheng, Gary Adamkiewicz, John D. Spengler, Chih-Da Wu

“…Data on phytoncide, including camphene and α-pinene, were directly collected from the study area. …”
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Fibrosis-4plus score: a novel machine learning-based tool for screening high-risk varices in compensated cirrhosis (CHESS2004): an international multicenter study by Bingtian Dong, Ruiling He, Shenghong Ju, Yuping Chen, Ivica Grgurevic, Jianzhong Ma, Ying Guo, Huizhen Fan, Qiang Yan, Chuan Liu, Huixiong Xu, Anita Madir, Kristian Podrug, Jia Wang, Linxue Qian, Zhengzi Geng, Shanghao Liu, Tao Ren, Guo Zhang, Kun Wang, Meiqin Su, Fei Chen, Sumei Ma, Liting Zhang, Zhaowei Tong, Yonghe Zhou, Xin Li, Fanbin He, Hui Huan, Wenjuan Wang, Yunxiao Liang, Juan Tang, Fang Ai, Tingyu Wang, Liyun Zheng, Zhongwei Zhao, Jiansong Ji, Wei Liu, Jiaojiao Xu, Bo Liu, Xuemei Wang, Yao Zhang, Qiong Yan, Hui Liu, Xiaomei Chen, Shuhua Zhang, Yihua Wang, Yang Liu, Li Yin, Yanni Liu, Yanqing Huang, Li Bian, Ping An, Xin Zhang, Shaoting Zhang, Jinhua Shao, Xiangman Zhang, Wei Rao, Chaoxue Zhang, Christoph Frank Dietrich, Won Kim, Xiaolong Qi

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The diagnostic and prognostic value of C1orf174 in colorectal cancer by Elham Nazari, Ghazaleh Khalili-Tanha, Ghazaleh Pourali, Fatemeh Khojasteh-Leylakoohi, Hanieh Azari, Mohammad Dashtiahangar, Hamid Fiuji, Zahra Yousefli, Alireza Asadnia, Mina Maftooh, Hamed Akbarzade, Mohammadreza Nassiri, Seyed Mahdi Hassanian, Gordon A Ferns, Godefridus J Peters, Elisa Giovannetti, Jyotsna Batra, Majid Khazaei, Amir Avan

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AI-powered literature search: some observations and concerns by Farooq Azam Rathore, Fareeha Farooq

“…It remains unclear for some search engines whether articles are chosen and recommended based on citation counts, impact factors, or other criteria. The algorithms behind AI tools may inherently approve of a certain type of content or styles of writing, which can affect the summaries produced.7 This data and algorithmic bias may be problematic for seasoned researchers who need to understand the basis for the information being generated by these AI tools. …”
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IDENTIFICATION OF TRAJECTORY INFORMATION BY APPLYING FUZZY AUTOMATIC CLASSIFICATION IN THE INFORMATION ASSOCIATION PROBLEM by A. V. Khizhniak, A. A. Belous, A. S. Bely

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