Artificial intelligence in ophthalmology: a bibliometric analysis of the 5-year trends in literature by Bosen Peng, Jiancheng Mu, Feng Xu, Wanyue Guo, Chuhuan Sun, Wei Fan

“…Key research hot spots are identified by keywords such as “deep learning,” “machine learning,” “convolutional neural network,” ”diabetic retinopathy,“ and ”ophthalmology.…”
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Optimized Flare Performance Analysis Through Multi-Modal Machine Learning and Temporal Standard Deviation Enhancements by Said Boumaraf, Pengfei Li, Muaz Al Radi, Fares Oussama Abdelhafez, Abderaouf Behouch, Khalid Yousef Al Awadhi, Hamad Karki, Sajid Javed, Jorge Dias, Naoufel Werghi

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AI-Driven Neuro-Monitoring: Advancing Schizophrenia Detection and Management Through Deep Learning and EEG Analysis by Elena-Anca Paraschiv, Lidia Băjenaru, Cristian Petrache, Ovidiu Bica, Dragoș-Nicolae Nicolau

“…This paper proposes a novel approach for detecting schizophrenia-related abnormalities using deep learning (DL) techniques applied to electroencephalogram (EEG) data. …”
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Comparative analysis of machine learning algorithms for predicting tibial intramedullary nail length from patient characteristics by Yujian Hui, Hengda Hu, Jinghua Xiang, Xingye Du

“…Abstract Objective This study aimed to evaluate the performance of five machine learning algorithms in predicting tibial intramedullary nail length using patient demographic data (gender, height, age, and weight), with the goal of developing a clinically relevant and accurate predictive model. …”
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Integrated multi-omics analysis and machine learning refine molecular subtypes and clinical outcome for hepatocellular carcinoma by Chunhong Li, Jiahua Hu, Mengqin Li, Yiming Mao, Yuhua Mao

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The Analysis of Students’ Learning Outcomes Majoring in Natural Science and Social Science at Accounting Education Study Program by Sahade Sahade, M. Yusuf A. Ngampo

“…Then, data were analyzed by descriptive statistical analysis. …”
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Analysis of Gender Differences in Facial Expression Recognition Based on Deep Learning Using Explainable Artificial Intelligence by Cristina Manresa-Yee, Silvia Ramis, José M. Buades

“…Data for machine learning play a fundamental role, therefore, understanding the relevancy of the data in the outcomes is of utmost importance. …”
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Deep Learning with 3D ResNets for Comprehensive Dual-Lane Speed Climbing Video Analysis by Xie Y., Mariano V.

“…While challenges such as data imbalance and limited generalization remain, this research provides a robust technical framework for speed climbing video analysis and lays the groundwork for broader applications in spatiotemporal modeling and intelligent sports analytics.…”
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Machine Learning Models with Neutrosophic Numbers for Cloud Security Analysis and Smart Grid Control of Renewable Energy by Ahmed E Fakhry, Mamdouh Gomaa, Ahmed A. Metwaly, Ahmed Abdelhafeez

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Breast Cancer Detection Analysis Using Different Machine Learning Techniques: South Iraq Case Study by Salma Abdulbaki Mahmood, Myssar Jabbar Hammood Al-Battbootti, Saad Shaheen Hamadi, Iuliana Marin, Costin-Anton Boiangiu, Nicolae Goga

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Mathematics and Machine Learning for Visual Computing in Medicine: Acquisition, Processing, Analysis, Visualization, and Interpretation of Visual Information by Bin Li, Shixiang Feng, Jinhong Zhang, Guangbin Chen, Shiyang Huang, Sibei Li, Yuxin Zhang

“…Machine learning has become a prominent tool for data analytics and problem-solving, which is the process of enabling computers to automatically learn from data and obtain certain knowledge, patterns, or input–output relationships. …”
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Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning by Yanzi Li, Cai Chen, Fuqiang Liu, Jian Wang

“…The production functions are assumed to be analyzed on basis of the random boundaries, which makes the analysis results inaccurate and unreliable. As a result, this paper proposes an analytical approach for agricultural total factor productivity based on the stochastic block model (SBM), which combines the benefits of statistics and machine learning. …”
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The learning curve of V-NOTES hysterectomy: a single-surgeon experience by François Charles, Mathieu Luyckx, Nathanael Dubois

“…No patient required conversion to laparotomy or conventional laparoscopy. The CUSUMot analysis demonstrated four phases in the learning curve: initiation (12 patients; mean OT, 66.17 ± 12.84 min), consolidation (41 patients; mean OT, 54.32 ± 13.96 min), complexification (54 patients; mean OT, 64.46 ± 25.48 min), and mastery (32 patients; mean OT, 54.5 ± 21.11 min). …”
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Treatment Effect Estimation in Survival Analysis Using Copula-Based Deep Learning Models for Causal Inference by Jong-Min Kim

“…This study compares the performance of the statistical methods—Copula-based deep learning with HT and IPTW weights, propensity score matching (PSM), and logistic regression—in estimating the treatment effect (ATE) using both simulated and real-world data. …”
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Study approaches mediate associations between learning environment and academic performance by Tore Bonsaksen, Amayra Tannoubi, Linda Stigen, Astrid Gramstad, Tove Carstensen, Gry Mørk

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Comparative Analysis of Gradient Descent Learning Algorithms in Artificial Neural Networks for Forecasting Indonesian Rice Prices by Rica Ramadana, Agus Perdana Windarto, Dedi Suhendro

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Evaluating Directed Acyclic Graphs with DAGMetrics: Insights from Tuber and Soil Microbiome Data by Pavel Averin, Ifigeneia Mellidou, Maria Ganopoulou, Aliki Xanthopoulou, Theodoros Moysiadis

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Analysis of Science Generic Skills in Animal Respiration Practicum: Is it Improved Through Guided Inquiry-based Learning? by Trya Adi Nur Destryani, Ria Yulia Gloria, Dede Cahyati Sahrir

“…Afterward, the collected data were analyzed using descriptive qualitative analysis. …”
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Sixth-grade students’ experiences of a digital game-based learning environment: A didactic analysis by Mustafa Gök, Mevlüt İnan

“…The research application lasted 75 minutes. The data analysis related to the application was carried out by describing the interaction between the students and the game at stages of TDS. …”
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Visual/Near-Infrared Spectroscopy Combined with Linear Discriminant Analysis and Machine Learning for Classification of Apple Damage by ZHANG Yu, ZHANG Chongyang, DUAN Xinxin, MA Shaoge, ZHAO Fu, WANG Juxia

“…This study investigated the combined application of visible/near-infrared (Vis-NIR) spectroscopy with linear discriminant analysis (LDA) and machine learning (ML) for the classification of apples with different degrees of damage. …”
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