TERMS OF RETINOBLASTOMA DIAGNOSIS IN PATIENTS WITH DISTINCT SIGNS AND SYMPTOMS by Tatiana V. Yanchenko, Elena V. Gromakina

“…We suggest clinical and diagnostic algorithm for early detection of Rb.…”
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Electronic Nose System Based on Metal Oxide Semiconductor Sensors for the Analysis of Volatile Organic Compounds in Exhaled Breath for the Discrimination of Liver Cirrhosis Patient... by Makhtar War, Benachir Bouchikhi, Omar Zaim, Naoual Lagdali, Fatima Zohra Ajana, Nezha El Bari

“…This study demonstrates the significant potential of e-nose technology towards VOCs analysis in exhaled breath, as a valuable tool for LC diagnosis. It also explores feature extraction methods and suitable algorithms for effectively distinguishing between LC patients and controls. …”
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Determination of high-confidence germline genetic variants in next-generation sequencing through machine learning models: an approach to reduce the burden of orthogonal confirmatio... by Muqing Yan, Qiandong Zeng, Zhenxi Zhang, Patricia Okamoto, Stanley Letovsky, Angela Kenyon, Natalia Leach, Jennifer Reiner

“…Further assessment using simulated false positive events as well as different combinations of quality features showed that model performance can be refined. …”
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An inductive learning-based method for predicting drug-gene interactions using a multi-relational drug-disease-gene graph by Jian He, Yanling Wu, Linxi Yuan, Jiangguo Qiu, Menglong Li, Xuemei Pu, Yanzhi Guo

“…Following the extraction of graph features by utilizing graph embedding algorithms, our next step was the retrieval of the attributes of individual gene and drug nodes. …”
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Utilizing Machine Learning Techniques for Cancer Prediction and Classification based on Gene Expression Data by Mariwan Mahmood Hama Aziz, Sozan Abdullah Mahmood

“…Detecting cancer early by examining gene expression data is vital for providing effective patient care. …”
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Pioneering machine learning techniques to estimate thermal conductivity of carbon-based phase change materials: A comprehensive modeling framework by Raouf Hassan, Alireza Baghban

“…A dataset of 482 samples, incorporating various nanoparticle types, concentrations, PCM types, and operating temperatures, was curated and refined using the Monte Carlo Outlier Detection algorithm. Extensive machine learning algorithms were explored; however, CatBoost, XGBoost, ANN, Random Forest, and Gradient Boosting emerged as the most accurate models. …”
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Predicting Mesothelioma Using Artificial Intelligence: A Scoping Review of Common Models and Applications by Malihe Ram MS, Mohammad Reza Afrash PhD, Khadijeh Moulaei PhD, Erfan Esmaeeli, Mohadeseh Sadat Khorashadizadeh, Ali Garavand PhD, Parastoo Amiri PhD, Azam Sabahi PhD

“…SVM, DT, and RF emerged as prominent models, achieving high accuracies ranging from 78.3% to 99.97%. Genetic algorithms, correlation-based algorithms, and Neural Networks were employed for risk factor identification and feature selection. …”
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Towards full integration of explainable artificial intelligence in colon capsule endoscopy’s pathway by Esmaeil S. Nadimi, Jan-Matthias Braun, Benedicte Schelde-Olesen, Smith Khare, Vinay C. Gogineni, Victoria Blanes-Vidal, Gunnar Baatrup

“…We developed a family of algorithms based on explainable deep neural networks (DNN) that detect polyps within a sequence of images, feed only those images containing polyps into two parallel independent networks to characterize, and estimate the size of important findings. …”
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Enhancing Regional Topsoil Total Nitrogen Mapping Through Differentiated Fusion of Ground Hyperspectral Data and Satellite Images Under Low Vegetation Cover by Rongpeng He, Jihua Meng, Yanfei Du, Zhenxin Lin, Xinyan You, Xinyu Gao

“…Therefore, a differentiated fusion of enhanced multispectral image bands (DFE_MSIBs) method combined with Random Forest (RF) algorithms was developed for spectral inversion of STN content. …”
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Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…Abstract Hearing loss poses immense burden worldwide and early detection is crucial. The accurate models identify high-risk groups, enabling timely intervention to improve quality of life. …”
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Design and trial of precision spraying system for weeds in winter wheat field at tillering stage by Bo Li, Peijie Guo, Yu Chen, Jun Chen, Haiying Wang, Jing Zhang, Zhixing Zhang

“…To improve the accuracy of weed detection, GCGS-YOLO is proposed as a weed target detection model, and we integrate the Global Context (GC) attention mechanism with the traditional C3 module to optimize the backbone feature extraction network, and introduce the GSConv module to improve the neck network. …”
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Deep Learning Approaches for Retinal Disease Identification in Fundus Imaging: A Comprehensive Overview by Ismael Abdulkareem Ali, Sozan Abdullah Mahmood

“…While in the medical field, manually detecting ocular pathology has significant difficulty. …”
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A Method for Aileron Actuator Fault Diagnosis Based on PCA and PGC-SVM by Wei-Li Qin, Wen-Jin Zhang, Chen Lu

“…Second, the data feature extraction is performed with dimension reduction using PCA. …”
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Advances in automated tongue diagnosis techniques by Marzia Hoque Tania, Khin Lwin, Mohammed Alamgir Hossain

“…This work reviews the recent advances in tongue diagnosis, which is a significant constituent of traditional oriental medicinal technology, and explores the literature to evaluate the works done on the various aspects of computerized tongue diagnosis, namely preprocessing, tongue detection, segmentation, feature extraction, tongue analysis, especially in traditional Chinese medicine (TCM). …”
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Towards a multi-modal Deep Learning Architecture for User Modeling by Ange Tato, Roger Nkambou

“…The resulting model was evaluated on a public multi-modal dataset, achieving better results than state-of-the-art algorithms for a similar task: opinion polarity detection. …”
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Evolving techniques in sentiment analysis: a comprehensive review by Mahander Kumar, Lal Khan, Hsien-Tsung Chang

“…This review comprehensively examines the evolving techniques in sentiment analysis, detailing foundational processes such as data gathering and feature extraction. It explores a spectrum of methodologies, from classical word embedding techniques and machine learning algorithms to recent contextual embedding and advanced transformer models like Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), and T5. …”
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Epidemiological, molecular, and evolutionary characteristics of G1P[8] rotavirus in China on the eve of RotaTeq application by Rui Peng, Rui Peng, Mengxuan Wang, Saleha Shahar, Guangping Xiong, Qing Zhang, Lili Pang, Hong Wang, Xiangyu Kong, Dandi Li, Zhaojun Duan

“…Phylogenetic and identity features of 11 genes were assessed by DNAStar and MEGA v.7.ResultsResults showed that the detection rate of G1P[8] in China from 2016 to 2018 was generally low with significant seasonality. …”
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Mapping hierarchical wetland characteristics by optical-SAR integration with collaborative spatial-spectral-temporal learning by Linwei Yue, Meiyue Wang, Chengpeng Huang, Qing Cheng, Qiangqiang Yuan, Huanfeng Shen

“…The evaluation results show that the overall accuracy of HiWet-DBNet reaches 88.51% and 88.61% in the dry and wet seasons, which is superior to the other solutions with only a single data source or insufficient fusion of multi-modal features. For the challenging task of submerged vegetation detection, the producer’s accuracy of HiWet-DBNet is improved by 1.70% to 16.59% compared with the VBI algorithm and state-of-art deep learning-based wetland classification methods.…”
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Moisture transport axes: a unifying definition for tropical moisture exports, atmospheric rivers, and warm moist intrusions by C. Spensberger, K. Konstali, T. Spengler

“…Here, we propose an algorithm that detects these various lines of moisture transport in instantaneous maps of the vertically integrated water vapour transport. …”
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Explainable Model of Fusion Network With Enhanced Optimization Approach for Tuberculosis Diagnosis by C. R. Dhivyaa, K. Nithya, C. Sathiya Kumar, R. Sudhakar

“…In the first approach, TrioFusionNet integrates three Convolutional models known as ResNet-50, InceptionV3, and EfficientB4 to detect deep features. After deep feature set creation, Principal Component Analysis is employed to decrease the feature dimensionality. …”
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