The Necessity of CT Hip Scans in the Investigation of Occult Hip Fractures and Their Effect on Patient Management by Thomas Gatt, Daniel Cutajar, Lara Borg, Ryan Giordmaina

“…The diagnostic challenge of negative plain radiography in the context of a previously ambulatory patient is increasing with the rise in geriatric trauma. …”
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Implementation and Evaluation of Wet Bulb Globe Temperature Within Non‐Urban Environments in the Community Land Model Version 5 by Jonathan R. Buzan

“…Using a conservative difference of ±0.3°C, 100% of land surface extreme sWBGT values and >77% extreme shaded conditions (FiWBGT) differ from WBGT. …”
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Efficiency of the Photoluminescent Method for Monitoring the Homogeneity of Feed Mixtures in Animal Husbandry by M. V. Belyakov, E. A. Nikitin, I. Yu. Efremenkov

“…The method of express quality control of mixing includes the following stages: initial calibration by the compound feed luminescence, sample preparation, mixture luminescence excitation, the luminescence flux registration, photo signal amplifiation and processing according to diagnostic algorithms, followed by either feed distribution or sequel mixing with repeated express control. …”
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Neurofibromatosis-Noonan syndrome: a prospective monocentric study of 26 patients and literature review by Didier Bessis, Dominique Vidaud, Pierre Meyer, Laurence Pacot, de La Villeon G, Adeline Alice Bonnard, Yline Capri, Christine Coubes, Fanchon Herman, Didier Lacombe, Nicolas Molinari, Laura Poujade, Agathe Roubertie, Julien Van Gils, Alain Verloes, David Geneviève, Hélène Cavé, Marjolaine Willems

“…Secondary objectives include evaluating inter-rater diagnostic agreement among experienced clinicians and assessing the utility of deep-learning algorithms (Face2Gene® [F2G]). …”
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Dynamic Multibody Modeling of Spherical Roller Bearings with Localized Defects for Large-Scale Rotating Machinery by Luca Giraudo, Luigi Gianpio Di Maggio, Lorenzo Giorio, Cristiana Delprete

“…In conclusion, the developed model represents a promising tool for generating useful datasets for training diagnostic and prognostic algorithms, thereby contributing to the improvement of predictive maintenance strategies in industrial settings. …”
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Towards a computer-assisted assessment of imitation in children with autism spectrum disorder based on a fine-grained analysis by Rujing Zhang, Jingying Chen, Xiaodi Liu, Yanling Gan, Guangshuai Wang

“…Then, three classic machine-learning algorithms were employed to explore whether the indicators could efficiently classify children with imitation difficulties. …”
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Potential use of saliva infrared spectra and machine learning for a minimally invasive screening test for congenital syphilis in infants by Deise Cristina Dal’Ongaro, Cicero Cena, Bruno Spolon Marangoni, Daniele A. Soares-Marangoni

“…Abstract Congenital syphilis is a global public health issue, and its diagnostic complexity poses a challenge to early treatment. …”
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Development of a host-signature-based machine learning model to diagnose bacterial and viral infections in febrile children by Fang Bai, Zelong Gong, Dong Cui, Xiaomei Zhang, Wenteng Hong, Yi Gao, Kai Lin, Weijie Chen, Lu Li, Juan Huang, Biying Zheng, Junfa Xu, Na Xiao

“…Subsequently, L1 regularization algorithms and variable significance analysis (multilayer perceptron) were used to simplify and rank the predictive features, and LCN2 (100.0%), IFI27 (84.4%), SLPI (63.2%), IFIT2 (44.6%) and PI3 (44.5%) were identified as the top predictors. …”
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Thermal Monitoring of an Internal Combustion Engine for Lightweight Fixed-Wing UAV Integrating PSO-Based Modelling with Condition-Based Extended Kalman Filter by Aleksander Suti, Gianpietro Di Rito, Giuseppe Mattei

“…The monitoring algorithm, being executable in real-time and capable of identifying incipient degradations of the thermal flow, demonstrates applicability for online diagnostics and predictive maintenance purposes.…”
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A dictionary learning approach with overlap for the low dose computed tomography reconstruction and its vectorial application to differential phase tomography. by Alessandro Mirone, Emmanuel Brun, Paola Coan

“…The functional depends on two free regularization parameters: a coefficient multiplying the sparsity-inducing L1 norm of the patch basis functions coefficients, and a coefficient multiplying the L2 norm of the differences between patches in the overlapping regions. …”
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Sex-Specific Cut-Offs for High-Sensitivity Cardiac Troponin: Is Less More? by Giulio Francesco Romiti, Roberto Cangemi, Filippo Toriello, Eleonora Ruscio, Susanna Sciomer, Federica Moscucci, Marianna Vincenti, Clara Crescioli, Marco Proietti, Stefania Basili, Valeria Raparelli

“…In the setting of acute coronary syndrome, the availability of high-sensitivity cardiac troponin assays (hs-cTn) has allowed for the development of algorithms aimed at rapidly assessing the risk of an ongoing myocardial infarction. …”
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Predicting Geostationary 40–150 keV Electron Flux Using ARMAX (an Autoregressive Moving Average Transfer Function), RNN (a Recurrent Neural Network), and Logistic Regression: A Com... by L. E. Simms, N. Yu. Ganushkina, M. Van derKamp, M. Balikhin, M. W. Liemohn

“…Abstract We screen several algorithms for their ability to produce good predictive models of hourly 40–150 keV electron flux at geostationary orbit (data from GOES‐13) using solar wind, Interplanetary Magnetic Field, and geomagnetic index parameters that would be available for real time forecasting. …”
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Diagnosis and activity prediction of SLE based on serum Raman spectroscopy combined with a two-branch Bayesian network by Qianxi Xu, Qianxi Xu, Qianxi Xu, Xue Wu, Xue Wu, Xue Wu, Xinya Chen, Ziyang Zhang, Jinrun Wang, Jinrun Wang, Zhengfang Li, Zhengfang Li, Zhengfang Li, Xiaomei Chen, Xiaomei Chen, Xiaomei Chen, Xin Lei, Xin Lei, Zhuoyu Li, Zhuoyu Li, Zhuoyu Li, Mengsi Ma, Mengsi Ma, Mengsi Ma, Chen Chen, Lijun Wu, Lijun Wu

“…A comparison was made between the proposed DBayesNet classification model and traditional machine and deep learning algorithms, including KNN, SVM, RF, LDA, ANN, AlexNet, ResNet, LSTM, and ResNet. …”
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Immunological biomarkers and gene signatures predictive of radiotherapy resistance in non-small cell lung cancer by Jie Lv, Chun-yang Yu, Yao-zu Xiong, Ting-ting Dai, Xiao-chu Hu, Peng Pan, Shun Yue, Chang-hua Yu

“…ResultsTGFBI showed the strongest correlation with NSCLC prognosis as indicated by a diagnostic nomogram. Additionally, significant differences in immune cell infiltration, particularly involving naive B cells and M0 macrophages, were noted between high-risk and low-risk patients. …”
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Metabolomic analysis in severe childhood pneumonia in the Gambia, West Africa: findings from a pilot study. by Evagelia C Laiakis, Gerard A J Morris, Albert J Fornace, Stephen R C Howie

“…<h4>Background</h4>Pneumonia remains the leading cause of death in young children globally and improved diagnostics are needed to better identify cases and reduce case fatality. …”
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Development and Validation of a Clinical Risk Model for Predicting Malignancy in Patients with Thyroid Nodules by Shiva Borzouei, Ali Safdari, Erfan Ayubi

“…Generally, there was no difference among the six ML algorithms in terms of prognostic performance; however, the prognostic parameters of GLM and LDA algorithms were higher than the others. …”
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Metabolomics and machine learning identify urine metabolic characteristics and potential biomarkers for severe Mycoplasma pneumoniae pneumonia by Lin Li, Wang haijun, Chen Tianyu, Wang Wenjing, Wang Zi, Cheng yibing

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Comparison of Cuff Leak Test, Laryngeal Ultrasonography, and Videolaryngoscopy for the prediction of post-extubation stridor by Rubina Khullar Mahajan, Apoorva Gupta, Parshotam Lal Gautam, Gunchan Paul, Vikalp Khatri

“…Cuff leak volume (CLV), leak volume fraction ratio (LVFR), and airway column width difference (ACWD) were noted. The grade of peri-laryngeal edema was noted with VL. …”
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Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional studyResearch in... by Cristina Saldivia-Siracusa, Eduardo Santos Carlos de Souza, Arnaldo Vitor Barros da Silva, Anna Luíza Damaceno Araújo, Caíque Mariano Pedroso, Tarcília Aparecida da Silva, Maria Sissa Pereira Sant'Ana, Felipe Paiva Fonseca, Hélder Antônio Rebelo Pontes, Marcos G. Quiles, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Syed Ali Khurram, Alexander T. Pearson, Mark W. Lingen, Luiz Paulo Kowalski, Keith D. Hunter, André Carlos Ponce de Leon Ferreira de Carvalho, Alan Roger Santos-Silva

“…Obtained results suggest that the adoption of DL models in healthcare could aid in diagnostic assistance and decision-making during clinical practice. …”
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Balancing accuracy and cost in machine learning models for detecting medial vascular calcification in chronic kidney disease: a pilot study by Urszula Bialonczyk, Malgorzata Debowska, Lu Dai, Abdul Rashid Qureshi, Leon Bobrowski, Magnus Soderberg, Bengt Lindholm, Peter Stenvinkel, Tomasz Lukaszuk, Jan Poleszczuk

“…Abstract Machine learning algorithms that integrate multiple biomarkers are increasingly used in disease detection, yet economic considerations are often overlooked. …”
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