Machine learning applications in forecasting patient satisfaction and clinical outcomes after carpal tunnel release: a retrospective study by Zohreh Manoochehri, Sara Manoochehri, Seyed Reza Bagheri, Alireza Abdi, Ehsan Alimohammadi

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Penerapan Decision Tree dan Random Forest dalam Deteksi Tingkat Stres Manusia Berdasarkan Kondisi Tidur by Sza Sza Amulya Larasati, Elok Nuraida Kusuma Dewi, Brahma Hanif Farhansyah, Fitra Abdurrachman Bachtiar, Fajar Pradana

“…The results of this research are expected to provide insights for other researchers in the same field and can serve as a reference for detecting ongoing stress. …”
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Root-Zone Salinity in Irrigated Arid Farmland: Revealing Driving Mechanisms of Dynamic Changes in China’s Manas River Basin over 20 Years by Guang Yang, Xuejin Qiao, Qiang Zuo, Jianchu Shi, Xun Wu, Alon Ben-Gal

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Construction and validation of acetylation-related gene signatures for immune landscape analysis and prognostication risk prediction in luminal breast cancer by Mengdi Zhu, Jinna Lin, Haohan Liu, Jingru Wang, Nianqiu Liu, Yudong Li, Hongna Lai, Qianfeng Shi

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Klasifikasi Katarak Berdasarkan Optic Disc Citra Fundus Smartphone: Perbandingan Ekstraksi Ciri Tekstur Dan Metode Neural Network by Muchtar Ali Setyo Yudono, Fabrobi Fazlur Ridha, Dani Mardiyana, Faturrohman Al-Ghozi, Aldi Maulana

“…The study evaluates the performance of three neural network algorithms: Backpropagation Neural Network (BPNN), Probabilistic Neural Network (PNN), and Radial Basis Function Neural Network (RBFNN) for cataract classification. …”
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Linear and Nonlinear Multivariate Classification of Iranian Bottled Mineral Waters According to Their Elemental Content Determined by ICP-OES by J.B. Ghasemi, E. Zolfonoun, R. Khosrokhavar

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Role of VATS-US in identifying and characterizing pulmonary nodules: a narrative review by Susana González-Suárez, Susana González-Suárez, Susana González-Suárez, María Grao Roca, Juan-Camilo Vivas, Alberto Jauregui, Alberto Jauregui

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Leader-Follower Game Mechanism and Strategy of Industrial Park Demand Response with User Aggregator by Zhangyi LI, Xin MA, Wei PEI, Liang ZHANG, Mingshuang LIU, Qiuhong LIANG

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Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing Data by Petrov Vladislav, Ustinov Stepan, Minaev Vasilii

“…Of the entire range of areas of fundamental and exploratory scientific research, the main attention within the framework of predictive and mineragenic studies is paid to solving the following problems: 1) allocation of lineaments (fault zones) based on processing of digital elevation models; 2) determination of hydraulically active fault structures for the period of ore formation based on tectonophysical reconstructions; 3) analysis of multispectral characteristics of pre-ore, ore-accompanying and post-ore metasomatites based on statistical processing of Landsat-8 satellite data; 4) assessment of fluid-dynamic settings of deposit formation based on data on the composition, properties and genesis of mineral-forming fluids. 5) creation of weight of evidence models based on statistical algorithms for processing data on the dynamics of ore-genetic processes. …”
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Physically Based and Data-Driven Models for Landslide Susceptibility Assessment: Principles, Applications, and Challenges by Chenzuo Ye, Hao Wu, Takashi Oguchi, Yuting Tang, Xiangjun Pei, Yufeng Wu

“…In contrast, data-driven models, primarily developed using machine learning and statistical algorithms, often provide acceptable predictive accuracy in assessing landslide susceptibility. …”
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Recent advances in deep learning for protein-protein interaction: a review by Jiafu Cui, Siqi Yang, Litai Yi, Qilemuge Xi, Dezhi Yang, Yongchun Zuo

“…With the inclusion of deep learning in PPI research, the field is undergoing transformative changes. …”
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Review of models for estimating 3D human pose using deep learning by Sani Salisu, Kamaluddeen Usman Danyaro, Maged Nasser, Israa M. Hayder, Hussain A. Younis

“…This study also outlines future research directions, offering a roadmap for both new and experienced researchers to further develop 3D HPE models using deep learning.…”
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Anomaly detection using machine learning and adopted digital twin concepts in radio environments by Mohamed Hussien Moharam, Omar Hany, Ahmed Hany, Amenah Mahmoud, Mariam Mohamed, Sohila Saeed

“…To validate the effectiveness of this framework, multiple machine learning algorithms based on traditional classifiers which are compared for their ability to detect anomalies, particularly jamming attacks. …”
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Machine Learning Applied to Improve Prevention of, Response to, and Understanding of Violence Against Women by Mariana Carolyn Cruz-Mendoza, Roberto Angel Melendez-Armenta, Juana Canul-Reich, Julio Muñoz-Benítez

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Autonomous Driving Road Environment Recognition with Multiscale Object Detection by Jeny J.R.V., Divya Phulari, Varsha Kolanu, Mrunalini Anantha, Irfan S.K.M.

“…Using cutting-edge deep learning techniques, this research presents a novel way for autonomous road environment classification and item detection. …”
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Optimization of Adaptive Observation Strategies for Multi-AUVs in Complex Marine Environments Using Deep Reinforcement Learning by Jingjing Zhang, Weidong Zhou, Xiong Deng, Shuo Yang, Chunwang Yang, Hongliang Yin

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A data mining technique for detecting malignant mesothelioma cancer using multiple regression analysis by Alali Abdulla Mousa Falah, Padmaja Dhyaram Lakshmi, Soni Mukesh, Khan Muhammad Attique, Khan Faheem, Ofori Isaac

“…The dataset, however, included both healthy and mesothelioma patients. Classification algorithms for MM illness diagnosis were carried out using computationally efficient data mining techniques. …”
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Single Vector Hydrophone DOA Estimation: Leveraging Deep Learning with CNN-CBAM by Fanyu ZENG, Yaning HAN, Hongyuan YANG, Dapeng YANG, Fan ZHENG

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Executive summary: indonesian guidelines on polycystic ovary syndrome management by Mila Maidarti, Achmad Kemal Harzif, Amalia Shadrina, Nafi'atul Ummah, Wiryawan Permadi

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Method for Preprocessing Video Data for Training Deep-Learning Models for Identifying Behavioral Events in Bio-Objects by Marina Barulina, Alexander Andreev, Ilya Kovalenko, Ilya Barmin, Eduard Titov, Danil Kirillov

“…Monitoring moving bio-objects is currently of great interest for both fundamental and practical research. The advent of deep-learning algorithms has made it possible to automate the qualitative and quantitative analysis of the behavior of bio-objects recorded in video format. …”
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