Survival analysis using machine learning in transplantation: a practical introduction by Andrea Garcia-Lopez, Maritza Jiménez-Gómez, Andrea Gomez-Montero, Juan Camilo Gonzalez-Sierra, Santiago Cabas, Fernando Giron-Luque

“…This study aims to provide an introduction to the application of the RSF model in survival analysis in kidney transplantation alongside a practical guide to develop and evaluate predictive algorithms. Methods We employed a RSF model to analyze a simulated dataset of kidney transplant recipients. …”
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Exploring the Realization of Creative Dimensions within the Metaverse: The Case of Tabriz Metropolis by Saied Jaffari namvar, Hossein Nazmfar, Ibrahim Taghav

“…</p> <p style="text-align: left;">The findings are from four sections, each of which divided into relevant sub-sections. In the first step, in order to determine the weight of the relative importance of the mentioned components, by asking 20 experts based on the algorithm of the analytical model of the preferential weighting ratio (SWARA), the weights of the indicators and sub-indices were extracted and ranked in the ARAS model. …”
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Two-Level Distributed Multi-Source Information Fusion Model for Aphid Monitoring and Forecasting in the Greenhouse by Xiaoyin Li, Lixing Wang, Min Dai, Yongji Zhang, Wei Su, Mingyou Wang, Hong Miao

“…To enhance the accuracy of regional environmental parameters, a weighted average algorithm employs environmental sensor data in the first level of fusion. …”
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An improved deep CNN-based freshwater fish classification with cascaded bio-inspired networks by Asadullah Shaikh, Wahidur Rahman, Kaniz Roksana, Tarequl Islam, Mohammad Motiur Rahman, Hani Alshahrani, Adel Sulaiman, Mana Saleh Al Reshan

“…The proposed methodology involves several key steps, including building a comprehensive dataset, extracting features from fish images using pre-trained Convolutional Neural Network (CNN) models, and employing typical ML approaches. …”
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Transfer learning based feature selection for feedforward neural network for speech emotion classifier by D. V. Krasnoproshin, M. I. Vashkevich

“…Proposed transfer learning approach consist in employing the backward-step selection algorithm for feature selection using statistical learning classifiers, the obtained subset of features than subsequently used to train feedforward neural networks. …”
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SOLUTION TO EVALUATION PROBLEM OF HIDDEN SEMI-MARKOV QP-MODELS by V. M. Deundyak, M. A. Zhdanova

“…The solution is based on Shun-Zheng Yu forward algorithm for a general hidden semi-Markov model. This approach differs from the traditional one and employs posterior probabilities. …”
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Unsupervised Rural Flood Mapping from Bi-Temporal Sentinel-1 Images Using an Improved Wavelet-Fusion Flood-Change Index (IWFCI) and an Uncertainty-Sensitive Markov Random Field (US... by Amin Mohsenifar, Ali Mohammadzadeh, Sadegh Jamali

“…In the first step, an improved wavelet-fusion flood-change index (IWFCI) is proposed. …”
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Image Robust Watermarking Method Based on DWT-SVD Transform and Chaotic Map by Weishuai Wu, Yujiao Dong, Guangyi Wang

“…The existing watermarking algorithms make it difficult to balance the invisibility and robustness of the watermark. …”
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Energy-Efficient UAV Trajectory Design and Velocity Control for Visual Coverage of Terrestrial Regions by Hengchao Li, Riheng Jia, Zhonglong Zheng, Minglu Li

“…Finally, the fourth step employs dynamic programming (DP) and geometry to jointly determine the UAV’s velocity control and complete trajectory during its task tour. …”
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An Analysis of the Design and Kinematic Characteristics of an Octopedic Land–Air Bionic Robot by Jianwei Zhao, Jiaping Gao, Mingsong Bao, Hao Zhai, Xu Pei, Zheng Jiang

“…An advanced kinematic analysis and simulation techniques are combined with inverse kinematic algorithms and dynamic planning to achieve a typical ‘Step-Wise Octopedal Dynamic Coordination Gait’ and different gait planning and optimization. …”
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Deep Learning-Based Draw-a-Person Intelligence Quotient Screening by Shafaat Hussain, Toqeer Ehsan, Hassan Alhuzali, Ali Al-Laith

“…To develop the artificial intelligence-based models, various deep learning algorithms were employed, including Convolutional Neural Network (CNN) and state-of-the-art CNN (Transfer Learning) models such as Mobile-Net, Xception, InceptionResNetV2, and InceptionV3. …”
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On the Prediction and Forecasting of PMs and Air Pollution: An Application of Deep Hybrid AI-Based Models by Youness El Mghouchi, Mihaela Tinca Udristioiu

“…A deep Nonlinear AutoRegressive Moving Average with eXogenous inputs (Deep-NARMAX) model was employed for multi-step-ahead forecasting. The best-performing models achieved R² values of 0.85 for PM_2.5 and 0.89 for PM₁₀, with low RMSE and MAPE scores, demonstrating high accuracy and generalizability. …”
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Unveiling the immune microenvironment of complex tissues and tumors in transcriptomics through a deconvolution approach by Shu-Hwa Chen, Bo-Yi Yu, Wen-Yu Kuo, Ya-Bo Lin, Sheng-Yao Su, Wei-Hsuan Chuang, I.-Hsuan Lu, Chung-Yen Lin

“…The output from DOCexpress_fastqc is seamlessly formatted with mySORT, a web application that employs a deconvolution algorithm to determine the immune content across 21 cell subclasses. …”
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MFSM-Net: Multimodal Feature Fusion for the Semantic Segmentation of Urban-Scale Textured 3D Meshes by Xinjie Hao, Jiahui Wang, Wei Leng, Rongting Zhang, Guangyun Zhang

“…The semantic segmentation of textured 3D meshes is a critical step in constructing city-scale realistic 3D models. …”
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A Hybrid Approach of DenseNet121 with Attention and Bi-LSTM for Yoga Pose Estimation by Aarthy K., Alice Nithya

“…Dynamic Histogram Equalization (DHE) is then employed to enhance image contrast, improving the visibility of key features within the images. …”
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RadiomiX for Radiomics Analysis: Automated Approaches to Overcome Challenges in Replicability by Harel Kotler, Luca Bergamin, Fabio Aiolli, Elena Scagliori, Angela Grassi, Giulia Pasello, Alessandra Ferro, Francesca Caumo, Gisella Gennaro

“…<b>Background/Objectives:</b> To simplify the decision-making process in radiomics by employing RadiomiX, an algorithm designed to automatically identify the best model combination and validate them across multiple environments was developed, thus enhancing the reliability of results. …”
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Integrating artificial neural networks, multi-objective metaheuristic optimization, and multi-criteria decision-making for improving MXene-based ionanofluids applicable in PV/T sol... by Tao Hai, Ali Basem, As’ad Alizadeh, Kamal Sharma, Dheyaa J. jasim, Husam Rajab, Abdelkader Mabrouk, Lioua Kolsi, Wajdi Rajhi, Hamid Maleki, Narinderjit Singh Sawaran Singh

“…In the final step, the TOPSIS technique, one of the well-known multi-criteria decision-making (MCDM) approaches, is employed to identify the desirable Pareto points. …”
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Does advancement in marker-less pose-estimation mean more quality research? A systematic review by Shivam Bhola, Shivam Bhola, Hyun-Bin Kim, Hyeon Su Kim, BonSang Gu, Jun-Il Yoo, Jun-Il Yoo

“…Despite the emergence of state-of-the-art keypoint-detection algorithms, the extent to which these tools are employed and the nature of their application in scientific research has yet to be systematically documented. …”
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Catalyzing early ovarian cancer detection: Platelet RNA-based precision screening by Eunyong Ahn, Se Ik Kim, Sungmin Park, Sarah Kim, Hyejin Lee, Yeochan Kim, Sangick Park, Suyeon Lee, Dong Won Hwang, Heeyeon Kim, HyunA Jo, Untack Cho, Juwon Lee, Cheol Lee, TaeJin Ahn, Yong-Sang Song

“…If integrated with current screening methods, our algorithm holds promise for identifying ovarian or endometrial cancer in its early stages.…”
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Innovative Tailored Semantic Embedding and Machine Learning for Precise Prediction of Drug-Drug Interaction Seriousness by Ayman Mohamed Mostafa, Alaa S. Alaerjan, Hisham Allahem, Bader Aldughayfiq, Meshrif Alruily, Alshaimaa A. Tantawy, Mohamed Ezz

“…We improved the performance by increasing the BioWordVec Indication Substance embedding specificity, a new creation constructed through transfer learning methodologies employed on the BioWordVec model. This approach employs not only the names of the drugs but also the indications for the drugs and the active substances, forming a highly semantic network capable of capturing multiple relations between drugs. …”
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