A prediction nomogram for residual after negative pressure aspiration for endogenic cesarean scar ectopic pregnancy: a retrospective study by Yan Lei, Na Zhang, Yu Liu, Xin Du

“…Receiver operating characteristic (ROC) analysis was performed to calculate the area under the curve, sensitivity, specificity, and other metrics to assess its discriminative performance. Clinical decision curves were constructed to evaluate clinical applicability and quantify the net benefit within a range of threshold probabilities. …”
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A Deep Learning Framework for the Classification of Brazilian Coins by Debabrata Swain, Viral Rupapara, Amro Nour, Santosh Satapathy, Biswaranjan Acharya, Shakti Mishra, Ali Bostani

“…Next, an RFE-CNN-based feature extractor extracts discriminative features from the coin images. We explore transfer learning from pre-trained models to enhance the model’s generalization capability, given limited data availability. …”
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Serum albumin-carcinoembryonic antigen ratio as an effective clinical tool for predicting recurrence and overall survival in patients with rectal cancer by Hailun Xie, Hailun Xie, Lishuang Wei, Shuangyi Tang, Jialiang Gan, Jialiang Gan

“…The predictive ability of the model was evaluated using the C-index and calibration curve, and its prognostic predictive abilities were compared to those of traditional Tumor Node Metastasis (TNM) stage using discriminant indices.ResultsA total of 736 patients with rectal cancer were included in the study. …”
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Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning by Hosna Tavakoli, Reza Rostami, Reza Shalbaf, Mohammad‐Reza Nazem‐Zadeh

“…Furthermore, we applied the methods for discriminating subtypes of schizophrenia. To streamline the feature set, various feature selection techniques were applied. …”
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Imprint of ancestral and modern threats in human mind – experience of fear, disgust, and anger by Eva Landová, Eva Landová, Jakub Polák, Jakub Polák, Markéta Janovcová, Iveta Štolhoferová, Šárka Peterková, Aleksandra Chomik, Daniel Frynta

“…Disgust does not respond to modern threat stimuli such as toxic substances or radioactivity as these evoke mainly fear and anger. A discriminant factor analysis classified nine out of 10 pandemic disgust vignettes into the ancestral disgust category, convincingly assigning the pandemic disgust threats to the ancestral type. …”
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Predictive Factors for Failure of Noninvasive Ventilation in Adult Intensive Care Unit: A Retrospective Clinical Study by Qimin Chen, Ming Liu, Bo Liu, Wei Li, Daixiu Gao, Lulu Xie, Yu Wu, Liang Li, Ying Liu, Ying Wang, Tang Yan, Yuanyi Liu, Yumei Cheng, Xu Liu, Feng Shen

“…A predictive model based on the risk factors could help to discriminate patients who are vulnerable to NIV failure.…”
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Freeze-Drying for the Reduction of Fruit and Vegetable Chain Losses: A Sustainable Solution to Produce Potential Health-Promoting Food Applications by Dario Donno, Giovanna Neirotti, Annachiara Fioccardi, Zoarilala Rinah Razafindrakoto, Nantenaina Tombozara, Maria Gabriella Mellano, Gabriele Loris Beccaro, Giovanni Gamba

“…Catechins, flavonols, and phenolic acids were the predominant and most discriminating classes in different products. The TPC values obtained in this study ranged from 366.86 ± 71.30 mg GAE/100 g DW (apple, MD) to 1077.13 ± 35.47 mg GAE/100 g DW (blueberry, MID) and 1102.25 ± 219.71 mg GAE/100 g DW (kaki, KD). …”
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Identification of novel autoantibodies in Sjögren’s disease by Fiona Engelke, Petra Budde, Salvatore De Vita, Thomas Dörner, Diana Ernst, Jan Gras, Harald Heidecke, Annika Loredana Kilian, Katja Kniesch, Ann-Sophie Lindemann, Luca Quartuccio, Jacob Ritter, Kai Schulze-Forster, Benjamin Seeliger, Hans-Dieter Zucht, Torsten Witte

“…We have developed a three and five marker panel for the detection of Ro/SSA negative patients, consisting of anti-FNBP4, anti-SNRPC, anti-CCL4, anti-M3 and anti-KDM6B, which had a sensitivity of up to 46% with a specificity of 95% (SjD vs. HC). Both panels discriminate these patients from HC, whereas the three-marker more effectively differentiates between Ro/SSA negative patients and NSS.DiscussionNovel autoantibodies will facilitate the diagnosis of Ro/SSA negative patients with SjD, in particular our predictive panel will be useful in the diagnosis and differentiation of these patients from healthy and NSS individuals in a clinical context. …”
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Determining the status of tertiary lymphoid structures in invasive pulmonary adenocarcinoma based on chest CT radiomic features by Ye Yu, Tianshu Yang, Pengfei Ma, Yan Zeng, Yongming Dai, Yicheng Fu, Aie Liu, Ying Zhang, Guanglei Zhuang, Yan Zhou, Huawei Wu

“…Conclusions The radiomics model has a higher AUC than the clinical model and effectively discriminates TLSs in patients with IA. Critical relevance statement This study demonstrates that the radiomics-based model can differentiate TLSs in patients with IA. …”
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Establishment and application of a one-step multiplex real-time PCR assay for detection of A, B, and C subtypes of avian metapneumovirus by Mingjun Su, Jiongze Cheng, Xiangwen Xu, Yijia Liu, Yulin Zhao, Yutao Wang, Xiaoxu Du, Jiale Ying, Junfang Yan, Huihua Zheng, Changyong Cheng, Jing Sun

“…In this study, we have developed a multiplex real-time PCR assay endowed with the capacity to simultaneously discriminate aMPV-A, aMPV-B, and aMPV-C. This method demonstrates remarkable specificity, selectively amplifying aMPV-A, aMPV-B, and aMPV-C without cross-reactivity with other common avian pathogens. …”
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Unraveling the association and regulatory role of miR-146b-5p in coronary artery disease by Xiaozhu Ma, Shuai Mei, Yi He, Qidamugai Wuyun, Li Zhou, Ziyang Cai, Qiushi Luo, Yi Wen, Jiangtao Yan

“…Receiver Operation Characteristic (ROC) analysis showed that the sensitivity and specificity of miR-146b-5p in discriminating CAD patients from non-CAD patients were meaningful. …”
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Behavior of SD-OCT Detectable Hyperreflective Foci in Diabetic Macular Edema Patients after Therapy with Anti-VEGF Agents and Dexamethasone Implants by Anne Rübsam, Laura Wernecke, Saskia Rau, Dominika Pohlmann, Bert Müller, Oliver Zeitz, Antonia M. Joussen

“…HF and hard exudates (HE) were discriminated by their appearance on fundus photographs and their size on OCT. …”
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Association between remnant cholesterol (RC) and endometriosis: a cross-sectional study based on NHANES data by Zeru Chen, Ruixuan Li, Jiajie Guo, Xiaorong Ye, Yang Zhou, Mingzhu Cao

“…The AUC of 0.614 suggests RC’s moderate ability to discriminate EMs, outperforming traditional markers like LDL-C in sensitivity and specificity. …”
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Integrating deep learning in public health: a novel approach to PICC-RVT risk assessment by Yue Li, Yue Li, Shengxiao Nie, Lei Wang, Dongsheng Li, Shengmiao Ma, Ting Li, Hong Sun

“…The DeepSurv model, in particular, shows excellent discriminative and calibration capabilities. Albumin levels, type of prefill sealant, and activated partial thromboplastin time are critical indicators for identifying and managing high-risk PICC-RVT patients.…”
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Tear glucose is associated with the presence and severity of diabetic retinopathy by Ningyao Cao, Lili Feng, Wei Xu, Fanglin He, Caiwen Xiao, Yan Liu, Weirong Xu, Jingjing Cui, Yuqian Guo, Lianqing Yao, Wenwen Xia, Fei Chen, Yong Li, Chuandi Zhou, Xiaofang Xu

“…The area under the curve (AUC) of the model integrating TG, the duration of diabetes and HbA1c was 0.76 (95% CI 0.69–0.84), indicating a fair discriminative ability of DR. Conclusion TG level was associated with the presence and the severity of DR. …”
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SVM directed machine learning classifier for human action recognition network by Dharmanna Lamani, Pramod Kumar, A Bhagyalakshmi, J. Maria Shanthi, Lakshmana Phaneendra Maguluri, Mohammad Arif, C Dhanamjayulu, Sathish Kumar. K, Baseem Khan

“…The use of traditional machine learning classifiers is done in order to further improve the discriminative capacity of the features that have been learned. …”
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Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA by Po-Ku Chen, Joung-Liang Lan, Yi-Ming Chen, Hsin-Hua Chen, Shih-Hsin Chang, Chia-Min Chung, Nurul H. Rutt, Ti-Myen Tan, Raja Nurashirin Raja Mamat, Nur Diana Anuar, Jonathan M. Blackburn, Der-Yuan Chen

“…Analysis of Cohort-2 dataset identified a panel of 8 biomarkers (TROVE2, SSB, NDE1, ZHX2, SH3GL1, CARD9, PTPN20, and KLHL12) with 80.6% specificity, 77.4% sensitivity, and 79.0% accuracy in discriminating poor from EULAR responders. Immunofluorescence assay validated that anti-TROVE2 antibody could highly predict ADAb development and poor EULAR response (AUC 0.79 and 0.89, respectively). …”
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Lower Circulating miR-122 Level in Patients with HNF1A Variant-Induced Diabetes Compared with Type 2 Diabetes by Xiuting Huang, Siqian Gong, Yumin Ma, Xiaoling Cai, Lingli Zhou, Yingying Luo, Meng Li, Wei Liu, Simin Zhang, Xiuying Zhang, Qian Ren, Yu Zhu, Xianghai Zhou, Rui Zhang, Ling Chen, Xueying Gao, Fang Zhang, Yanai Wang, Xueyao Han, Linong Ji

“…The area under the curve of the receiver operating characteristic curve for miR-122 to discriminate HNF1A-DM and T2DM was 0.687 (95% CI: 0.52–0.86, P=0.07). …”
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Diagnostic Capability of Pattern Electroretinogram and Three Circumpapillary Retinal Nerve Fiber Layer Thickness Circle Diameter Scans in Glaucoma Suspects by Tirsi A, Tsai J, Abizadeh A, Kacaj D, Procyk O, Gliagias V, Leung N, Yang H, Park SC, Tello C

“…MagD showed the foremost diagnostic capability (AUC = 0.81), followed by Mag (AUC = 0.799) and MagD/Mag (AUC = 0.762).Conclusion: Global, superior, and inferior RNFLT in 3.5 and 4.1 mm diameters, and MagD performed best in discriminating GS from controls, suggesting that a larger scan of 4.1 mm may be equally useful in glaucoma diagnosis as the conventional 3.5 mm diameter. …”
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Predictive Value of Albumin to Fibrinogen Ratio and CALLY Index for Diagnosis of Ulcerative Colitis and Mucosal Healing After Vedolizumab Treatment by Su K, Xiao S, Wang M, Wang K, Fan Q, Sha S, Cheng Y, Liu X, Shi H

“…For Vedolizumab treatment, the non-MH group had significantly lower baseline AFR and CALLY index compared to the MH group; the AUC for baseline AFR and CALLY index discriminating the MH group from the non-MH group were 0.665 and 0.721, respectively. …”
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