Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision me... by Yutong Fang, Rongji Zheng, Yefeng Xiao, Qunchen Zhang, Junpeng Liu, Jundong Wu

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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Validation of a data-driven motion-compensated PET brain image reconstruction algorithm in clinical patients using four radiotracers by Ole L. Munk, Anders B. Rodell, Patricia B. Danielsen, Josefine R. Madsen, Mie T. Sørensen, Niels Okkels, Jacob Horsager, Katrine B. Andersen, Per Borghammer, Joel Aanerud, Judson Jones, Inki Hong, Sven Zuehlsdorff

“…In the research cohort, MoCo images consistently matched or surpassed the standard image quality even in cases with minimal head movement, and the MoCo algorithm never led to degraded image quality. Conclusion The PET brain MoCo reconstruction algorithm was robust and worked well for four different tracers with markedly different uptake patterns. …”
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The Comprehensive Analysis of Weighted Gene Co-Expression Network Analysis and Machine Learning Revealed Diagnostic Biomarkers for Breast Implant Illness Complicated with Breast Ca... by Huang Z, Wang H, Pang H, Zeng M, Zhang G, Liu F

“…Enrichment analysis, the protein–protein interaction network (PPI), and machine learning algorithms were performed to explore the hub genes. …”
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Depression Analysis and Detection Using Machine Learning: Incorporating Gender Differences in a Comparative Study by Marina Galanina, Anna Rekiel, Anna BaCzyk, Bozena Kostek

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Single Cell Transcriptomics Genomics Based on Machine Learning Algorithm: Constructing and Validating Neutrophil Extracellular Trap Gene Model in COPD by Yu J, Xiao T, Pan Y, He Y, Tan J

“…At present, there are still few studies to explore the characteristics of NET in different chronic obstructive pulmonary disease (COPD) patients. …”
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Developing supervised machine learning algorithms to classify lettuce foliar tissue samples into interpretation zones for 11 plant essential nutrients by Patrick Veazie, Hsuan Chen, Kristin Hicks, Jake Holley, Nathan Eylands, Neil Mattson, Jennifer Boldt, Devin Brewer, Roberto Lopez, Brian Whipker

“…This study examines four different machine learning algorithms (J48, random forest [RF], sequential minimal optimization [SMO], and multilayer perceptron [MLP]) by two different cross‐validation strategies (10‐fold and 66% split) to determine if machine learning can be utilized to accurately classify foliar tissue samples within corresponding nutrient ranges. …”
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Fine-Grained Classification of Pressure Ulcers and Incontinence-Associated Dermatitis Using Multimodal Deep Learning: Algorithm Development and Validation Study by Alexander Brehmer, Constantin Seibold, Jan Egger, Khalid Majjouti, Michaela Tapp-Herrenbrück, Hannah Pinnekamp, Vanessa Priester, Michael Aleithe, Uli Fischer, Bernadette Hosters, Jens Kleesiek

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Efficacy of histological and cytological examination under different methods of sampling biopsies at endoscopy in patients with respiratory pathology by I. V. Liskina, O. I. Shpak, L. M. Zagaba, V. B. Bychkovskiy, M. F. Yatsina

“…The article presents the value of different methods of sampling biopsy during endoscopy with cytological and morphological examination of biopsy material in the diagnostic algorithm of various pathological processes of the respiratory system. …”
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Characterisation of Human Exhaled Breath Gases for Chronic Obstructive Pulmonary Disease Utilising an E-Nose Sensor and the Bi-LSTM Algorithm by Nilakshi Maruti Mule, Dipti Durgesh Patil

“…Research has shown that the VOC profiles of COPD patients differ from those of healthy controls, indicating that the E-nose system may serve as a viable diagnostic tool for COPD patients. …”
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Performance analysis of DC-DC Buck converter with innovative multi-stage PIDn(1+PD) controller using GEO algorithm by Mostafa Jabari, Davut Izci, Serdar Ekinci, Mohit Bajaj, Ievgen Zaitsev

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Analysis of imaging differences between high-resolution CT and digital radiography chest films in pneumoconiosis screening by Lijuan LIU, Fenghong WANG

“…HRCT enables systematic observation of the evolution and progression of pneumoconiosis, providing reliable evidence for diagnosis.ObjectiveTo provide reliable evidences for the early screening of pneumoconiosis, By analyzing the imaging difference between HRCT and DR chestfilms in pneumoconiosis screening.MethodsSix casting workers in a casting forging company suspected of early stage of pneumoconiosis through regular occupational health examination screening were recruited , and 64 rows of spiral CT thin layer were scanned and reconstructed by high-resolution bone algorithm. …”
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Selection of memory clinic patients for CSF biomarker assessment can be restricted to a quarter of cases by using computerized decision support, without compromising diagnostic acc... by Hanneke F M Rhodius-Meester, Ingrid S van Maurik, Juha Koikkalainen, Antti Tolonen, Kristian S Frederiksen, Steen G Hasselbalch, Hilkka Soininen, Sanna-Kaisa Herukka, Anne M Remes, Charlotte E Teunissen, Frederik Barkhof, Yolande A L Pijnenburg, Philip Scheltens, Jyrki Lötjönen, Wiesje M van der Flier

“…Computer-supported prediction restricts CSF testing to only 26% of cases, without compromising diagnostic accuracy.…”
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Detecting depression in patients with coronary heart disease: a diagnostic evaluation of the PHQ-9 and HADS-D in primary care, findings from the UPBEAT-UK study. by Mark Haddad, Paul Walters, Rachel Phillips, Jacqueline Tsakok, Paul Williams, Anthony Mann, André Tylee

“…Areas under the curves (AUC) (standard error) were 0.95 (0.01) and 0.88 (0.02) for the PHQ-9 and HADS-D, and 0.91 (0.02) for PHQ-9 using the categorical algorithm. Statistically significant differences between AUCs of the PHQ-9 and the HADS-D favoured the former. …”
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Epidemiological and clinical aspects of syphilis incidence in the Russian Federation and the Republic of Uzbekistan: comparative analysis by Margarita R. Rakhmatulina, Delya F. Porsokhonova, Elena Yu. Novoselova, Avaz Sh. Inoyatov

“…As a result of the study of regulatory documents regulating algorithms and principles of management of patients with syphilis, differences in laboratory diagnostic algorithms and treatment regimens were revealed, namely lower dosages of drugs and shorter treatment courses for patients with syphilis in the Republic of Uzbekistan compared with those in the Russian Federation.…”
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STUDY OF PREDICTION AND CLASSIFICATION MODELS IN THE PROBLEMS OF DIABETES AMONG PATIENTS WITH A STROKE IN DIFFERENT LIVING CONDITIONS by Nural Huliiev, Maksym Peretiaha, Artem Khovrat, Denys Teslenko, Alexei Nazarov

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Sex differences in shoulder acromiohumeral contact surface arc length on three-dimensional computed tomography imaging by Xi Chen, Tangzhao Liang, Chang Liu, Jianhua Ren, Shouwen Su, Xiangyu Long, Xiaopeng Yin, Yanbin Chen, Shihai Jiang, Kun Wang

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Complete Blood Count and Monocyte Distribution Width–Based Machine Learning Algorithms for Sepsis Detection: Multicentric Development and External Validation Study by Andrea Campagner, Luisa Agnello, Anna Carobene, Andrea Padoan, Fabio Del Ben, Massimo Locatelli, Mario Plebani, Agostino Ognibene, Maria Lorubbio, Elena De Vecchi, Andrea Cortegiani, Elisa Piva, Donatella Poz, Francesco Curcio, Federico Cabitza, Marcello Ciaccio

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Transbronchial lung cryobiopsy for diagnosing interstitial lung disease: a cross-sectional, comparative study by Min Yu, Xuefeng Xu, Xiaoyan Xin, Shangwen Yang, Yihua Wang, Yonglong Xiao, Shenyun Shi, Xuebing Feng

“…Conclusions This study indicated that the clinical applicability of TBLC in ILD diagnostic algorithms, with a diagnostic yield of 85.0% and an acceptable safety profile.…”
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A patient-centric chest pain management approach utilizing a high sensitivity Troponin-I assay by Abby E. Roetger, Christopher D. McKinney, De B. Winter III, Charmaine Lewis, Kristopher Swiger, Claire M. Corbett, Gregory Hall, Adam David, Austin Gratton

“…Before implementation, the conventional Seimens troponin Vista assay was utilized without a defined algorithmic approach. Bivariate analyses were performed comparing the time periods to determine differences in patient discharge dispositions, length of stay, outcomes, and rate of diagnostic cardiac catheterization. …”
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Machine Learning-Based Scoring System to Predict the Risk and Severity of Ataxic Speech Using Different Speech Tasks by Bipasha Kashyap, Pubudu N. Pathirana, Malcolm Horne, Laura Power, David J. Szmulewicz

“…In this study, we introduce a fully automated objective algorithm that uses significant acoustic features from time, spectral, cepstral, and non-linear dynamics present in microphone data obtained from different repeated Consonant-Vowel (C-V) syllable paradigms. …”
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