Prominent events in the development of a simultaneous multidiagnostic system with synthetic peptides by Oscar Noya, Henry Bermúdez, Diana Pachón, Belkisyolé Alarcón de Noya, Diana Ortiz-Princz, Flor Helene Pujol, Sandra Losada

“…This method allows the simultaneous detection of antibodies against 26 different agents with only a few microliters of sera, plasma, or saliva. …”
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Vibration, current, torque, RPM dataset for multiple fault conditions in industrial-scale electric motors under randomized speed and load variationsMendeley DataMendeley DataMendel... by Wonho Jung, Junho Kim, Kangmin Jang, Sung-Hyun Yun, Daeguen Lim, Minje Jin, Yong-Hwa Park

“…The inclusion of multi-fault, multi-severity, and variable-condition data makes it especially suitable for training generalizable diagnostic algorithms in both academic and industrial contexts. …”
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THE APPROVAL OF COMPLEX TREATMENT EFFECTIVENESS OF GENERALIZED PERIODONTITIS FOR THE PATIENTS AFTER TRANSMITTED CORONAVIRUS DISEASE AND REMAIN ON REHABILITATION by T.I. Matviykiv, M.M. Rozhko

“…Examination of areas compromised by generalized periodontitis and abutment teeth based on the obtained periotestometric data of tooth mobility, indicates a significant reduction in inflammation and strengthening of the ligaments and is a highly informative diagnostic method. …”
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Repeatability and agreement of three biometers measuring corneal keratometry and astigmatism in eyes with cataract and high myopia by Haisheng Zhou, Tong Bao, Shuchan Li, Yunlei Pang, Qinglei Shao, Lifeng Wang, Lihua Yin, Jinli Wang, Na Hu, Yuanyuan Qi, Bozhou Zhang

“…Further research is needed to refine measurement algorithms and optimize clinical accuracy.…”
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Deep-Learning-Based Computer-Aided Grading of Cervical Spinal Stenosis from MR Images: Accuracy and Clinical Alignment by Zhiling Wang, Xinquan Chen, Bin Liu, Jinjin Hai, Kai Qiao, Zhen Yuan, Lianjun Yang, Bin Yan, Zhihai Su, Hai Lu

“…<b>Objective:</b> This study aims to apply different deep learning convolutional neural network algorithms to assess the grading of cervical spinal stenosis and to evaluate their consistency with clinician grading results as well as clinical manifestations of patients. …”
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Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech by Julianna Olah, Win Lee Edwin Wong, Atta-ul Raheem Rana Chaudhry, Omar Mena, Sunny X. Tang

“…Our study aimed to (1) identify an optimal assessment approach for the online and remote collection of speech, in the context of assessing the psychosis spectrum and evaluate whether a fully automated, speech-based machine learning (ML) pipeline can discriminate among different conditions on the schizophrenia-bipolar spectrum (SSD-BD-SPE), help-seeking comparison subjects (MDD), and healthy controls (HC) at varying layers of analysis and diagnostic complexity. …”
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Epidemiological association of the COVID-19 pandemic on Mycoplasma pneumoniae infections in children in Tianjin, China: a single-centre retrospective study (2017–2024) by Wei Wang, Lu Wang, Run Guo, Yun Bo, Yingxue Zou, Hualei Cui

“…These temporal and demographic patterns emphasise the necessity of incorporating epidemiological surveillance into diagnostic algorithms for childhood respiratory infections, particularly in post-pandemic settings. …”
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Comparison of self-collected and healthcare worker-collected rectovaginal swabs for group B streptococcus detection in pregnancy using PCR with a commercial collection-enrichment d... by Iva Kukovica, Neža Omahen, Nika Klobučar, Martina Bučar, Anita Franko Rutar, Tina Perme, Tina Perme, Miha Lučovnik, Miha Lučovnik, Samo Jeverica, Samo Jeverica

“…Performance characteristics were calculated and compared between different diagnostics test algorithms using McNemar’s test for paired samples.ResultsOverall, GBS was detected in 18% (95% CI 13–23%; n = 40) of swabs A and 19% (95% CI 14–25%; n = 43) of swabs B. …”
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AI Efficiency in Dentistry: Comparing Artificial Intelligence Systems with Human Practitioners in Assessing Several Periodontal Parameters by Oana-Maria Butnaru, Monica Tatarciuc, Ionut Luchian, Teona Tudorici, Carina Balcos, Dana Gabriela Budala, Ana Sirghe, Dragos Ioan Virvescu, Danisia Haba

“…However, further validation in clinical settings is necessary to address limitations such as algorithmic bias and atypical cases. AI integration in dentistry can enhance diagnostic precision and patient outcomes while reducing variability in clinical assessments.…”
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Machine Learning and Experimental Validation Reveal MYH11 as a Novel Prognostic Biomarker and Therapeutic Target in Bladder Cancer by Tan Z, Chen X, Fu S, Huang Y, Li H, Gong C, Lv D, Yang C, Wang J, Ding M, Wang H

“…This study aimed to explore the potential molecular mechanisms of BCa using multi-omics and single-cell analysis.Methods: First, differential analysis of transcriptome data related to BCa from public databases was performed, and a risk model was then developed using 101 different machine learning algorithms to determine prognostic genes, followed by independent prognostic analysis to construct a nomogram. …”
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Depression and Anxiety Screening for Pregnant Women via Free Conversational Speech in Naturalistic Condition by Rafael T. Sousa, Gustavo D. M. Silva, Paula L. L. Pinto, Juliano Backes, Amanda S. Mota, Thiago M. Paixao, Maria G. S. Teixeira, Wilian H. Hisatugu, Anilton S. Garcia, Kelly S. Prado, Rodrigo S. Dias, Marco A. Galletta, Hermano Tavares

“…The research involved collecting conversational speech samples from pregnant women attending a high-risk pregnancy outpatient service, employing smartphones to capture naturalistic speech in everyday contexts. Machine learning algorithms were utilized combined with different audio feature sets to analyze these recordings in conjunction with PHQ-4 questionnaire scores. …”
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Classification and risk assessment of ovarian-adnexal lesions using parametric and radiomic analysis of co-registered ultrasound-photoacoustic tomographic images by Yixiao Lin, Quing Zhu

“…Additionally, statistics-based radiomic algorithms were applied to quantify differences in the lesion texture on US-PAT images. …”
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Artificial Neural Network Text Generation as a New Type of Masking the Authorship by Ogorelkov Igor', Mahaeva Elizaveta

“…As a result, experts have to be able to tell the difference between natural and generative tests to establish authorship. …”
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What happens between first symptoms and first acute exacerbation of COPD – observational study of routine data and patient survey by Alex Bottle, Alex Adamson, Xiubin Zhang, Benedict Hayhoe, Jennifer K Quint

“…However, there is limited understanding of what prompts a diagnosis, how long this takes from symptom onset and the different approaches to clinical management by primary care professionals. …”
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Oral contrast-enhanced ultrasonographic features and radiomics analysis to predict NIH risk stratification for gastrointestinal stromal tumors by Fan Yang, Fan Yang, Fan Yang, Fan Yang, Chun-wei Liu, Dai Zhang, Dai Zhang, Dai Zhang, Dai Zhang, Hai-Ling Wang, Hai-Ling Wang, Hai-Ling Wang, Hai-Ling Wang, Xi Wei, Xi Wei, Xi Wei, Xi Wei, Mo Yang, Mo Yang, Mo Yang

“…The combined model showed a better diagnostic performance.…”
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Correlations between blood group and Rh factor in families and autism spectrum disorder: A comprehensive analysis by Adil Abdul-Rehman Siddiq Al-Salihy

“…Using chi-square tests, logistic regression analysis, and machine learning algorithms, the findings revealed that the O + blood group was the most prevalent across all groups. …”
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Development of a Predictive Model of Occult Cancer After a Venous Thromboembolism Event Using Machine Learning: The CLOVER Study by Anabel Franco-Moreno, Elena Madroñal-Cerezo, Cristina Lucía de Ancos-Aracil, Ana Isabel Farfán-Sedano, Nuria Muñoz-Rivas, José Bascuñana Morejón-Girón, José Manuel Ruiz-Giardín, Federico Álvarez-Rodríguez, Jesús Prada-Alonso, Yvonne Gala-García, Miguel Ángel Casado-Suela, Ana Bustamante-Fermosel, Nuria Alfaro-Fernández, Juan Torres-Macho

“…XGBoost, LightGBM, and CatBoost algorithms were used to train different prediction models, which were subsequently validated in a hold-out dataset. …”
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Synergistic detection of E. coli using ultrathin film of functionalized graphene with impedance spectroscopy and machine learning by Amrit Kumar, Shweta Mishra, R. K. Gupta, V. Manjuladevi

“…Machine learning (ML) algorithms applied to raw impedance data improved detection precision and reliability, enabling automated and accurate analysis. …”
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Prediction of Early Diagnosis in Ovarian Cancer Patients Using Machine Learning Approaches with Boruta and Advanced Feature Selection by Tuğçe Öznacar, Tunç Güler

“…Random Forest and CatBoost’s performances demonstrated significant differences in contrast to other algorithms (respectively, AUC 0.94% and 0.95%). …”
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Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data by Erli Wu, Xuan Yin, Feng Liang, Xianqing Zhou, Jiamin Hu, Wanting Yuan, Feihan Gu, Jingxin Zhao, Ziyang Gao, Ming Cheng, Shouxiang Yang, Lei Zhang, Qingqing Wang, Qingqing Wang, Xiaoyu Sun, Xiaoyu Sun, Wei Shao, Wei Shao

“…By combining the bulk transcriptome and applying machine learning methods, we identified several potential ICD-related hub genes, which were then used to build diagnostic models. Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”
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