Towards rigorous dataset quality standards for deep learning tasks in precision agriculture: A case study exploration by A. Carraro, G. Saurio, F. Marinello

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Automated Detection of Central Retinal Artery Occlusion Using OCT Imaging via Explainable Deep Learning by Ansgar Beuse, Daniel Alexander Wenzel, MD, Martin Stephan Spitzer, MD, Karl Ulrich Bartz-Schmidt, MD, Maximilian Schultheiss, MD, Sven Poli, MD, Carsten Grohmann, PhD, MD

“…Our model followed a multiclass approach, distinguishing among the 3 different classes: control, CRAO, and differential diagnoses. The evaluation was conducted by the “one vs. all” area under the receiver operating characteristics curve (AUC) method. …”
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Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

“…Setting Participants were recruited from 179 United Kingdom primary care practices. …”
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Effectiveness of an electronic clinical decision support system in improving the management of childhood illness in primary care in rural Nigeria: an observational study by Marek Kwiatkowski, Rodolfo Rossi, Torsten Schmitz, Fenella Beynon, Capucine Musard, Marco Landi, Daniel Ishaya, Jeremiah Zira, Muazu Muazu, Camille Renner, Edwin Emmanuel, Solomon Gideon Bulus

“…Objectives To evaluate the impact of ALgorithm for the MANAgement of CHildhood illness (‘ALMANACH’), a digital clinical decision support system (CDSS) based on the Integrated Management of Childhood Illness, on health and quality of care outcomes for sick children attending primary healthcare (PHC) facilities.Design Observational study, comparing outcomes of children attending facilities implementing ALMANACH with control facilities not yet implementing ALMANACH.Setting PHC facilities in Adamawa State, North-Eastern Nigeria.Participants Children 2–59 months presenting with an acute illness. …”
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Identifikasi Dini Curah Hujan Berpotensi Banjir Menggunakan Algoritma Long Short-Term Memory (Lstm) Dan Isolation Forest by Ahmad Wijayanto, Aris Sugiharto, Rukun Santoso

“…The Isolation Forest algorithm is then used to automatically identify rainfall with flood potential. …”
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Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis by Lu Xing, Tao Wu, Li Yu, Nian Zhou, Zhao Zhang, Yunjing Pu, Jinnan Wu, Hong Shu

“…GSE13355, GSE14905, and GSE73894 were collected from the gene expression omnibus (GEO) database. …”
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Epidemiological trends and age-period-cohort effects on periodontal diseases incidence across the BRICS from 1992 to 2021 by Xiaochan Wang, Yuting Xu, Xiangming Ma, Ruixing Nan, Yuhang Wu, Peiyu Cheng

“…Distinct national trajectories, shaped by varying socioeconomic, cultural, and historical frameworks, highlight that public health initiatives must be meticulously customized to mitigate and control the periodontal diseases burden across diverse settings.…”
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Open source automated insulin delivery systems: experience of russian patients by V. V. Klimontov, K. S. Shishin

“…However, 79% of them had technical difficulties when setting up the system for the first time, 46% had difficulty understanding the settings of the algorithm / program, and 35% spent a lot of effort studying the system. …”
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Remaining Useful Life Prediction and Fault Diagnosis of Rolling Bearings Based on Short-Time Fourier Transform and Convolutional Neural Network by Shuang Zhou, Maohua Xiao, Petr Bartos, Martin Filip, Guosheng Geng

“…The rolling bearing life-cycle datasets from the Intelligent Management System were applied to verify the proposed life prediction method, showing that its accuracy reaches 99.45%, and the prediction effect is good. Multiple sets of validation experiments were conducted to verify the proposed fault diagnosis method with the open datasets from Case Western Reserve University. …”
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The Choice of Training Data and the Generalizability of Machine Learning Models for Network Intrusion Detection Systems by Marcin Iwanowski, Dominik Olszewski, Waldemar Graniszewski, Jacek Krupski, Franciszek Pelc

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Dunes Identification Based on Attention Mechanism With Dual-Branch Codec by Zhaobin Wang, Yan Li, Yue Shi, Yaonan Zhang, Xuejun Guo

“…A series of ablation experiments, effectiveness analyses, and comparative studies across different algorithms on two datasets were conducted to evaluate the generalization ability of dual-branch codec network based on attention mechanism across diverse datasets. …”
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Constructing a predictive model for acute mastitis in lactating women based on machine learning by Liujing Zhu, Zuyan Huang, Yan Chen, Guangqiu Li, Liwen Liu

“…This study employed a retrospective case-control study approach and collected relevant data from 369 patients with acute mastitis and 447 healthy controls. …”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…To complement the random field modeling, an enhanced PSO algorithm is proposed for 3D slope stability analysis. …”
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Acceptability of an AI-enabled family module in a mobile app for enhanced diabetes management: Patient and family perspectives by Sungwon Yoon, Rena Lau, Yu Heng Kwan, Huiyi Liu, Razeena Sahrin, Jie Kie Phang, Yichi Zhang, Nicholas Graves, Lian Leng Low

“…Regarding module features, participants appreciated algorithm-driven nudges and in-app interactions but emphasized the importance of controlling the frequency of nudges. …”
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Development and Investigation of Vision System for a Small-Sized Mobile Humanoid Robot in a Smart Environment by Amer Tahseen Abu-Jassar, Hani Attar, Ayman Amer, Vyacheslav Lyashenko, Vladyslav Yevsieiev, Ahmed Solyman

“…A structure of information interaction between hardware modules is proposed, and a connection scheme is developed, on the basis of which a model of a computer vision system is assembled for research, with the required algorithmic and software for solving the problem. To ensure the high speed of the computer vision system based on the ESP32-CAM module, the neural network was improved by replacing the Visual Geometry Group 16 (VGG-16) network as the base network for extracting the functions of the Single Shot Detector (SSD) network model with the tiny-YOLO lightweight network model, which made it possible to preserve the multidimensional structure of the network model feature graph, resulting in increasing the detection accuracy, while significantly reducing the amount of calculations generated by the network operation, thereby significantly increasing the detection speed, due to a limited set of objects. …”
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The value of radiomics features of white matter hyperintensities in diagnosing cognitive frailty: a study based on T2-FLAIR imaging by Qinmei Liao, Xihao Hu, Zhiqiong Jiang, Xiaoyun Huang, Jiacheng Guo, Yuanzhong Zhu, Wenjing He

“…Methods The present study conducted a retrospective analysis on 147 patients (77 with CF, 70 in the control group). …”
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Deep‐HH: A deep learning‐based high school student hidden hunger risk prediction system by Yang Yang, Zheng Zhang, Huake Cao, Yuchen Zhang, Minao Wang, Ning Zhang

“…We used six ML algorithms (i.e., deep‐learning neural network [DNN], random forest, support vector machine, extreme gradient boosting, gradient boosting decision tree, and k‐nearest neighbor) to fit the training set using five‐fold cross‐validation, with hyperparameter tuning performed via Bayesian optimization. …”
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Energy Optimisation of Industrial Limestone Grinding Using ANN by Dagmara Kołodziej, Patryk Bałazy, Paweł Knap, Krzysztof Lalik, Damian Krawczykowski

“…In the next phase, black-box optimisation was performed using Bayesian and genetic algorithms to identify optimal mill operating settings. …”
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Cervical cancer prediction using machine learning models based on routine blood analysis by Jie Su, Hui Lu, Ruihuan Zhang, Na Cui, Chao Chen, Qin Si, Biao Song

“…In this restrospective study, medical records of patients from 2013 to 2023 were collected. A total of 2,503 patients diagnosed with CC were included in the case group, while the control group was composed of 3,794 patients without apparent signs of the disease, which included women with other gynecological conditions as well as healthy individuals undergoing routine check-ups. …”
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Development and validation of interpretable machine learning models for postoperative pneumonia prediction by Bingbing Xiang, Yiran Liu, Shulan Jiao, Wensheng Zhang, Shun Wang, Mingliang Yi

“…This study aimed to develop and validate a predictive model for postoperative pneumonia in surgical patients using nine machine learning methods.ObjectiveOur study aims to develop and validate a predictive model for POP in surgical patients using nine machine learning algorithms. By evaluating the performance differences among these machine learning models, this study aims to assist clinicians in early prediction and diagnosis of POP, providing optimal interventions and treatments.MethodsRetrospective data from electronic medical records was collected for 264 patients diagnosed with postoperative pneumonia and 264 healthy control surgical patients. …”
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