Ekyeyo Mobile Application by Nkuba, Blair, Kansiime, Daniel

“…The app incorporates advanced search algorithms, tailored job recommendations, and streamlined candidate screening to improve job-matching accuracy. …”
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Acoustic-based machine learning approaches for depression detection in Chinese university students by Yange Wei, Yange Wei, Shisen Qin, Fengyi Liu, Rongxun Liu, Yunze Zhou, Yuanle Chen, Xingliang Xiong, Wei Zheng, Guangjun Ji, Yong Meng, Fei Wang, Fei Wang, Ruiling Zhang

“…Among five machine learning algorithms, LDA model demonstrated the highest classification performance, with an AUC of 0.771. …”
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Pulmonary arterial hypertension in systemic lupus erythematosus: identification of risk factors and haemodynamics characteristics in a multicentre retrospective cohort by Carlo Alberto Scirè, Alessandra Bortoluzzi, Micaela Fredi, Matthias Schneider, Veronica Codullo, Carlomaurizio Montecucco, Alain Meyer, Ilaria Cavazzana, Lorenzo Cavagna, Franco Franceschini, Andreas Schwarting, Konstantinos Triantafyllias, Gamal Chehab, Christina Düsing, Jutta Richter, Ettore Silvagni, Oliver Sander, Giovanni Zanframundo, Claudia Bracaglia, Matthieu Canuet, Stefano Ghio, Rebecca Fischer, Emiliano Marasco, Sezgin Sahin, Lisa Keller, Marianne Riou, Stefanie Keymel

“…The variables we identified could be used to implement a screening algorithm to identify patients with SLE at risk of developing PAH.…”
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Prospective Validation and Usability Evaluation of a Mobile Diagnostic App for Obstructive Sleep Apnea by Pedro Amorim, Daniela Ferreira-Santos, Marta Drummond, Pedro Pereira Rodrigues

“…Current guidelines recommend the development of clinical prediction algorithms in screening prior to PSG. A recent intuitive and user-friendly tool (OSABayes), based on a Bayesian network model using six clinical variables, has been proposed to quantify the probability of OSA. …”
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Investigating the Complexity of Multidimensional Symptom Experiences in Patients With Cancer: Systematic Review of the Network Analysis Approach by Vincent Richard, Allison Gilbert, Emanuela Pizzolla, Giovanni Briganti

“…Several NA approaches were used: network visualization (n=1), Bayesian network (n=1), pairwise Markov random field and IsingFit method (n=1), unregularized Gaussian graphical model (n=2), regularized partial correlation network (n=6), network visualization and community NA (n=1), network visualization and Walktrap algorithm (n=1), undirected network model with the Fruchterman-Reingold and edge-betweenness approaches (n=4), biased correlation and concise pattern diagram (n=1), extended Bayesian information criterion graphical LASSO method (n=3), cross-lagged panel network (n=1), and unspecified NA (n=3). …”
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Machine Learning and Interpretability Study for Predicting 30-Day Unplanned Readmission Risk of Schizophrenia: A Retrospective Study by Tan Y, Chen G, Wang S, Zhan X, Cheng R, Qiao L, Zhang Z, Liu Y

“…Models were constructed after screening variables using the multiple linear regression and feature importance methods. …”
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Acetic Acid Production from Aspergillus terreus Isolated from Some Agricultural Soils Collected from Selected Locations within the North Gondar Zone, Amhara Region, Ethiopia by Kidist Alemayehu, Tamene Milkessa Jiru, Nega Berhane

“…A sequence similarity of 98.5% to A. terreus isolate LL2 (KIA) was obtained by comparing the Aspergillus isolate to a reference sequence in the GenBank using the BLAST algorithm. It can be concluded from this study that A. terreus isolated from agricultural soil in the north Gondar zone of Ethiopia could produce more acetic acid using barely straw as a substrate.…”
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Risk factors for osteoporosis in men aged 40 years or older: the results of the program «Osteoscreening-Russia» by O. A. Nikitinskaya, N. V. Toroptsova, E. L. Nasonov

“…The survey was conducted using a unified questionnaire. Screening also involved a densitometric study of distal forearm bone mineral density using a peripheral X-ray osteodensitometer (Osteometer Meditech DTX-200). …”
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A computer-driven ventilator liberation protocol in pediatric patients: a single-center pilot randomized controlled trial by Song Chen, Changxue Xiao, Xue Lu, Min Liao, Chengjun Liu, Feng Xu, Jing Li

“…The test group underwent ventilator liberation driven by a computerized algorithm combining protocolized screening, air leak testing, and spontaneous breathing testing. …”
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Progress and challenges of artificial intelligence in lung cancer clinical translation by Erjia Zhu, Amgad Muneer, Jianjun Zhang, Yang Xia, Xiaomeng Li, Caicun Zhou, John V. Heymach, Jia Wu, Xiuning Le

“…Abstract Artificial intelligence (AI) algorithms, such as convolutional neural networks and transformers, have significantly impacted cancer care. …”
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Analysis of risk factors of acute respiratory failure after radical resection of esophageal cancer by two methods by LEI Xiuwen, ZHU Xiaolei, TIAN Long

“…The combination of the two methods is conducive to the joint screening of risk factors for ARF after radical resection for esophageal cancer, and the three rules are more valuable in guiding clinical intervention." …”
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Psychometric properties of the German version of the Traumatic Grief Inventory-Self Report Plus (TGI-SR+) by Julia Treml, Viktoria Schmidt, Elmar Braehler, Matthias Morfeld, Anette Kersting

“…Despite the same name, both versions of PGD differ in symptom count, content, and diagnostic algorithm. A single instrument to screen for both PGD diagnoses is critical for bereavement research and care. …”
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Identification of retinol dehydrogenase 10 as a shared biomarker for metabolic dysfunction-associated steatotic liver disease and type 2 diabetes mellitus by Fangyu Li, Rui Li, Hongjun Deng

“…The LASSO algorithm and ROC curve identified Retinol Dehydrogenase 10 (RDH10) as the best diagnostic gene for MASLD and T2DM. …”
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LABORATORY OF CLINICAL IMMUNOLOGY N.V. SKLIFOSOVSKY RESEARCH INSTITUTE FOR EMERGENCY MEDICINE (HISTORY AND PRESENT) by M. A. Godkov, G. V. Bulava

“…During 45 years of work of immunological service formed the algorithm of the adequate immunological screening was formed, number of innovative methods of diagnosis was developed, the ideology of post-test counseling of patients by immunologists was created, mathematical methods of storage, modeling and processing of research results was introduced. …”
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Identifying Safeguards Disabled by Epstein-Barr Virus Infections in Genomes From Patients With Breast Cancer: Chromosomal Bioinformatics Analysis by Bernard Friedenson

“…EBV-transformed human mammary cells accelerate breast cancer when transplanted into immunosuppressed mice, but the virus can disappear as malignant cells reproduce. If this model applies to human breast cancers, then they should have genome damage characteristic of EBV infection. …”
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Dielectric tensor prediction for inorganic materials using latent information from preferred potential by Zetian Mao, WenWen Li, Jethro Tan

“…We develop an equivariant readout decoder to predict total, electronic, and ionic dielectric tensors while preserving O(3) equivariance, and benchmark its performance against state-of-the-art algorithms. Virtual screening of thermodynamically stable materials from Materials Project for two discovery tasks, high-dielectric and highly anisotropic materials, identifies promising candidates including Cs2Ti(WO4)3 (band gap E g = 2.93eV, dielectric constant ε = 180.90) and CsZrCuSe3 (anisotropic ratio α r = 121.89). …”
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Sialyltransferase-related genes as predictive factors for therapeutic response and prognosis in cervical cancer by Jia Shao, Can Zhang, Yaonan Tang, Aiqin He, Xiangyan Cheng

“…Cox regression analysis and “glmnet” R package were applied to establish the relevant risk model. “MCPcounter” R package, ESTIMATE algorithm and TIMER online tools were used to depict the tumor immune microenvironment in CC. …”
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Plasma metabolite biomarker identification study for the early detection of gastric cancer by Juan Zhu, Yida Huang, Bin Liu, Xue Li, Li Yuan, Le Wang, Kun Qian, Yingying Mao, Lingbin Du, Xiangdong Cheng

“…Ultra-performance liquid chromatography–mass spectrometry–based metabolomics methods were used to characterize the subjects’ plasma metabolic profiles and to screen and validate the GC biomarkers. Five machine learning algorithms (neural network, support vector machine, ridge regression, lasso regression and Naïve Bayes) were used to build a diagnostic model. …”
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Application of artificial intelligence in the diagnosis of malignant digestive tract tumors: focusing on opportunities and challenges in endoscopy and pathology by Yinhu Gao, Peizhen Wen, Yuan Liu, Yahuang Sun, Hui Qian, Xin Zhang, Huan Peng, Yanli Gao, Cuiyu Li, Zhangyuan Gu, Huajin Zeng, Zhijun Hong, Weijun Wang, Ronglin Yan, Zunqi Hu, Hongbing Fu

“…Results In the field of endoscopy, multiple deep learning models have significantly improved detection rates in real-time polyp detection, early gastric cancer, and esophageal cancer screening, with some commercialized systems successfully entering clinical trials. …”
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Machine learning-based ultrasound radiomics for predicting risk of recurrence in breast cancer by Wei Fan, Hao Cui, Xiaoxue Liu, Xudong Zhang, Xinran Fang, Junjia Wang, Zihao Qin, Xiuhua Yang, Jiawei Tian, Lei Zhang

“…The receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA) curves were used to evaluate the model’s clinical applicability and predictive performance.ResultsA total of 12 ultrasound radiomics features were screened, of which wavelet.LHL first order Mean features weighed more and tended to have a high risk of recurrence. …”
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