Identification of climate-sensitive disease incidences in vietnam: A longitudinal retrospective analysis of infectious disease rates between 2014 and 2022 by Cuong Quoc Hoang, Quang Phuong Huynh Nguyen, Thao Phuong Huynh Nguyen, Hieu Trung Nguyen, Linh Thuy Hoang, Giang Huong Vu, Woong-Ki Kim, Hai Duc Nguyen

“…Method: We conducted a retrospective longitudinal study spanning 108 consecutive months from 2014 to 2022 in Can Tho, Vietnam to identify common infectious diseases (excluding tuberculosis, HIV, and COVID-19) and their associations with climate change and determine which common diseases presented concurrently with the COVID-19 period using multivariate linear regression, receiver operating characteristic (ROC) curve analysis, Bayesian kernel machine regression (BKMR) and orthogonal partial least squares discriminant analysis. Result: The five infectious diseases with the highest average incidence rates per 100,000 people were diarrhea; hand, foot, and mouth disease (HFMD); dengue fever; viral hepatitis; and influenza. …”
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A Study of Volatile Organic Compounds in Patients with Obstructive Sleep Apnea by Chuan Hao Gui, Zhunan Jia, Zihao Xing, Fuchang Zhang, Fang Du, Alex Chengyao Tham, Ming Yann Lim, Yaw Khian Chong, Agnes Si Qi Chew, Khai Beng Chong

“…To as-sess the differences in VOC concentrations between OSA patients and control subjects, the Wilcoxon rank-sum test was employed. partial least squares discriminant analysis (PLS-DA) analysis and heatmap plot was conducted to visualize the differentiation between OSA patients and control subjects based on their VOC profiles.In order to further investigate the correlation between identified biomarkers and the severity of OSA measured by Apnea–Hypopnea Index (AHI), regression analysis was conducted between biomarkers and AHI Index. …”
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Can aortic valve calcium score predict a need for permanent pacemaker implantation after transcatheter aortic valve implantation? by Helene Eltchaninoff, Eric Durand, Christophe Tron, Charles Fauvel, Thomas Barbe, Thibaut Hemery, Guillaume Le Pessec, Najime Bouhzam, Nicolas Bettinger, Julie Burdeau, Jade Makke, Quentin Laissac, Jean-Nicolas Dacher

“…AVCS had an incremental discriminative value (C-index 0.79 vs 0.77, LR test p=0.036) over and above traditional PPM risk factors. …”
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Construction and Validation of a Major Depression Risk Predictive Model for Patients with Coronary Heart Disease: Insights from NHANES 2005–2018 by Li-xiang Zhang, Shan-bing Hou, Fang-fang Zhao, Ting-ting Wang, Ying Jiang, Xiao-juan Zhou, Jiao-yu Cao

“…The areas under the receiver operating characteristic (ROC) curve in the nomogram model for both the development and validation cohorts were 0.816 (95% confidence interval (CI): 0.776–0.857) and 0.765 (95% CI: 0.699–0.832), respectively, indicating the model possessed strong discriminative ability. Brier scores in the development and validation cohorts were 0.107 and 0.127, respectively, both well below the 0.25 threshold, demonstrating good calibration. …”
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Stock price prediction with attentive temporal convolution-based generative adversarial network by Ying Liu, Xiaohua Huang, Liwei Xiong, Ruyu Chang, Wenjing Wang, Long Chen

“…This approach employs a GAN framework to generate stock price data using an attentive temporal convolutional network as a generator, whereas a CNN-based discriminator evaluates the authenticity of the data. …”
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Characterization of microbiota signatures in Iberian pig strains using machine learning algorithms by Lamiae Azouggagh, Noelia Ibáñez-Escriche, Marina Martínez-Álvaro, Luis Varona, Joaquim Casellas, Sara Negro, Cristina Casto-Rebollo

“…However, the most genetically distant animals, the purebreds, were more easily discriminated using the ML models. The classification of the two Iberian strains reached the highest mean AUROC of 0.83 using Support Vector Machine (SVM) model. …”
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Integrating the A2DS2 Score with 24-Hour ASPECTS and red cell distribution width for enhanced prediction of stroke-associated pneumonia following intravenous thrombolysis: model de... by Sarawut Krongsut, Nat Na-Ek, Atiwat Soontornpun, Niyada Anusasnee

“…The combined A2DS2-MFP model demonstrated excellent discriminative performance (AuROC: 0.917) compared to the traditional A2DS2 model (AuROC: 0.868) and the model with continuous predictors (AuROC: 0.888). …”
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Utility of Visceral Adiposity Index and Lipid Accumulation Products to Define Metabolically-Unhealthy Polycystic Ovary Syndrome in Asian Indian Women - A Cross Sectional Study by R. A. Shreenidhi, Reeta Mahey, Monika Rajput, Rohitha Cheluvaraju, Ashish D. Upadhyay, Jai Bhagwan Sharma, Garima Kachhawa, Neerja Bhatla

“…Results: VAI and LAP had good ability to correctly discriminate MU-PCOS from MH-PCOS (area under the curve [AUC] [95% confidence interval (CI)]: 0.89 [0.82–0.95]) and (AUC [95% CI [0.81–0.92] =0.86) using ROC, respectively. …”
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Assessing validity and reliability of the Transition Shock Scale for Undergraduate Nursing Students (TSS, Chinese version) in associate degree nursing students by Huiting Weng, Ziwei Ding, Li Yang, Bo Zhang, Yuanyuan Luo, Qin Wang

“…Thus, the TSS (Chinese version) discriminant and concurrent validities were confirmed. …”
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Association between weight-adjusted waist-index and symptoms of sleep apnea in US adults: results from 2015–2018 national health and nutrition examination survey by Edmore Madondo, Paddington T. Mundagowa, Ayesha Mukhopadhyay, Debra Bartelli, Yu Jiang, Fawaz Mzayek

“…This study investigated the association between WWI and symptoms of sleep apnea among United States adults and compared WWI’s discriminative power with BMI, WtHR, WHR, and WC in the evaluation of symptoms of sleep apnea. …”
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CECT-Based Radiomic Nomogram of Different Machine Learning Models for Differentiating Malignant and Benign Solid-Containing Renal Masses by Qian L, Fu B, He H, Liu S, Lu R

“…Furthermore, the radiomic nomogram, which incorporated sex, age, alcohol consumption history, and the radiomic signature, exhibited excellent discriminative performance, yielding an AUC of 0.973 in the training cohort and 0.900 in the test cohort.Conclusion: The radiomic nomogram based on CECT offers a promising and noninvasive approach for distinguishing malignant from benign solid renal masses. …”
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Self-assessment of didactic performance of psychology and education professors in Mexico and Peru by Aldo Bazán-Ramírez, Walter Capa-Luque, Roberto Chávez-Nava, Mónica C. Dávila-Navarro, Homero Ango-Aguilar, Edmundo Hervias-Guerra, Catalina Bello-Vidal

“…Evidence of convergent and discriminant validity was also acceptable. The reliability for the overall score of the questionnaire as well as for the interactive episodes evidenced McDonald’s ordinal alpha and omega coefficients ≥0.94 and H coefficient ≥ 0.95. …”
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Ion Chromatography Based Urine Amino Acid Profiling Applied for Diagnosis of Gastric Cancer by Jing Fan, Jing Hong, Jun-Duo Hu, Jin-Lian Chen

“…A diagnostic model was constructed to discriminate gastric cancer from healthy individuals and another diagnostic model for clinical staging by principal component analysis. …”
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Non-Invasive Cancer Detection Using Blood Test and Predictive Modeling Approach by Tarawneh AS, Al Omari AK, Al-khlifeh EM, Tarawneh FS, Alghamdi M, Alrowaily MA, Alkhazi IS, Hassanat AB

“…The random forest (RF) classifier, followed by linear discriminant analysis (LDA) and support vector machine (SVM), achieved the highest prediction accuracy (ranging from 0.69 to 0.72 depending on the scenario and method investigated), reliably distinguishing between malignant and benign conditions. …”
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Features and predictive value of 6-min walk test outcomes in interstitial lung disease: an observation study using wearable monitors by Jiaying Li, Xiaobing Wu, Xiaoyan Li, Miaozhen Deng, Xinyin Liang, Huiqun Wei

“…SpO2 at the third minute was the most valuable predictor of patients’ lung function. 6MWD and SpO2 changes were more discriminative in subtypes.…”
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Identification of Crucial lncRNAs for Luminal A Breast Cancer through RNA Sequencing by Xinjian Jia, Hai Lei, Xuemei Jiang, Ying Yi, Xue Luo, Junyan Li, Yu Chen, Sha Liu, Chengcheng Yang

“…The protein expression results of TUBB3, MCM2, MYOC, FN1, S100A7, and TFF1 were consistent with the mRNA expression result COL10A1, LEP, PLIN1, PGM5-AS1, and TRHDE-AD1 were capable of discriminating luminal A breast cancer and normal controls. …”
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Kombinasi Feature Selection Fisher Score dan Principal Component Analysis (PCA) untuk Klasifikasi Cervix Dysplasia by Krisan Aprian Widagdo, Kusworo Adi, Rahmat Gernowo

“…Only relevant and discriminant features can provide an accurate classification result. …”
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Optic Nerve Head Hemoglobin Levels in Glaucoma: A Structural and Functional Correlation Study by Janaina A. G. Rocha, Diego T. Dias, Maria Betânia C. Lemos, Fábio N. Kanadani, Augusto Paranhos, Carolina P. B. Gracitelli, Tiago S. Prata

“…Software Laguna ONhE was used to estimate the amount of ONH Hb and to determine the glaucoma discriminant function (GDF) index. Scatter plots were constructed, and regression analysis was used to investigate the correlations between GDF, average pRNFL thickness, and VF mean deviation (VFMD) index values. …”
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A Data-Driven Deep Learning Framework for Prediction of Traffic Crashes at Road Intersections by Mengxiang Wang, Wang-Chien Lee, Na Liu, Qiang Fu, Fujun Wan, Ge Yu

“…In Phase I we extract discriminative latent features called <i>topological-relational features (tr-features)</i>, of intersections using a neural network model by exploiting topological information of the road network and various relationships amongst nearby intersections. …”
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Low Serum miR-607 Level as a Potential Diagnostic and Prognostic Biomarker in Patients of Pancreatic Ductal Adenocarcinoma: A Preliminary Study by Dawei Jiang, Xiangfei Yuan, Jianqi Ni, Lan Shen, Min Cai, Liu Xu

“…Furthermore, the area under the curve (AUC) of serum miR-607 for discriminating PDAC patients was 0.785 with a sensitivity of 0.647 and a specificity of 0.772, which was better than those for CA19-9 (AUC: 0.702, sensitivity: 0.607, specificity: 0.736) and CEA (AUC: 0.648, sensitivity: 0.542, specificity: 0.670). …”
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