Novel integrative models to predict the severity of inflammation and fibrosis in patients with drug-induced liver injury by Yue Zhang, Chuan Lu, Jingying Xu, Qiqi Ma, Mei Han, Li Ying

“…This study aims to develop novel integrative models to identify DILI-associated liver inflammation and fibrosis, and compare the predictive values with previously developed indexes.MethodsA total of 72 DILI patients diagnosed as DILI through liver biopsy were enrolled in this study. …”
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Development and validation of a Jordan-specific risk score for type 2 diabetes mellitus by Julia A Critchley, Laith J Abu-Raddad, Yousef Khader, Susanne F Awad, Asalah Alareeki, Kamel M Ajlouni

“…The positive and negative predictive values were 29.7% (95% CI: 28.4 to 31.0%) and 94.0% (95% CI: 93.3 to 94.7%), with 42.7% of Jordanians at high risk for diabetes. …”
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Validity of a minimally invasive autopsy tool for cause of death determination in pediatric deaths in Mozambique: An observational study. by Quique Bassat, Paola Castillo, Miguel J Martínez, Dercio Jordao, Lucilia Lovane, Juan Carlos Hurtado, Tacilta Nhampossa, Paula Santos Ritchie, Sónia Bandeira, Calvino Sambo, Valeria Chicamba, Mamudo R Ismail, Carla Carrilho, Cesaltina Lorenzoni, Fabiola Fernandes, Pau Cisteró, Alfredo Mayor, Anelsio Cossa, Inacio Mandomando, Mireia Navarro, Isaac Casas, Jordi Vila, Khátia Munguambe, Maria Maixenchs, Ariadna Sanz, Llorenç Quintó, Eusebio Macete, Pedro Alonso, Clara Menéndez, Jaume Ordi

“…Concordance in the category of disease obtained by the two methods was evaluated by the Kappa statistic, and the sensitivity, specificity, and positive and negative predictive values of the MIA diagnoses were calculated. …”
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Concurrent validity of the ages and stages questionnaires with Bayley Scales of Infant Development-III at 2 years – Singapore cohort study by Pratibha Keshav Agarwal, Huichao Xie, Anu Sathyan Sathyapalan Rema, Michael J. Meaney, Keith M. Godfrey, Victor Samuel Rajadurai, Lourdes Mary Daniel

“…Sensitivity, specificity, positive (PPV) and negative (NPV) predictive values were calculated. Correlations between the ASQ-3 and Bayley-III domains were evaluated using Pearson coefficients. …”
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Neutrophil-related immune-inflammatory biomarkers influence the early progression of medial medullary infarction by Li-Min Li, Hao Cai

“…Receiver operating characteristic (ROC) curves were used to evaluate the predictive values of blood-derived indicators.ResultsThe white blood cell (WBC) count, neutrophil count, monocyte count, low-density lipoprotein cholesterol (LDL-C) level, total cholesterol (TC) concentration, WBC-to-high-density lipoprotein cholesterol (HDL-C) ratio (WHR), neutrophil-to-HDL-C ratio (NHR), monocyte-to-HDL-C ratio (MHR), monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were significantly greater in patients with MMI than in HCs (p < 0.05). …”
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THE CRITERIA FOR LYMPH NODE METASTATIC DISEASE IN UTERINE CERVIX CANCER PATIENTS BASED ON MRI FINDINGS by E. G. Zhuk, I. A. Kosenko

“…The sensitivity and specificity with a cutoff of ≥0.8cm were 68 % (CI 48.3‑82.9) and 80 % (CI 63.8‑90.3), respectively; the positive and negative predictive values were 71 % and 78 %, respectively; and the accuracy was 75 % (CI 62.7‑84.3). …”
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Predicting vaginal delivery after labor induction using machine learning: Development of a multivariable prediction model by Iolanda Ferreira, Joana Simões, João Correia, Ana Luísa Areia

“…Prediction of vaginal delivery obtained good discrimination in the independent validation data (AUROC = 0.794, 95% CI 0.783–0.805), showing high positive and negative predictive values (PPV and NPV) of 0.752 and 0.793, respectively, high specificity (0.910) and sensitivity (0.766). …”
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Artificial Intelligence–Enabled ECG Screening for LVSD in LBBB by Hak Seung Lee, MD, Sooyeon Lee, MD, Sora Kang, MS, Ga In Han, MS, Ah-Hyun Yoo, MS, Jong-Hwan Jang, PhD, Yong-Yeon Jo, PhD, Jeong Min Son, MD, Min Sung Lee, MD, MS, Joon-myoung Kwon, MD, MS, Kyung-Hee Kim, MD, PhD

“…All models were externally validated on 1,334 ECGs from another hospital, with performance assessed by area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and predictive values. Results: In external validation, the transfer learning model achieved the highest AUROC (0.903; 95% CI: 0.887-0.918), closely followed by the general model (0.899; 95% CI: 0.883-0.915); the difference was not significant. …”
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A Novel Electrocardiographic Approach for Accurate Diagnosis of Prior Inferior Myocardial Infarction by Hailei Liu, MD, Thien Tan Tri Tai Truyen, MD, Harpriya Chugh, MSHS, Kyndaron Reinier, PhD, Ashkan Ehdaie, MD, Eugenio Cingolani, MD, Archana Ramireddy, MD, Eric D. Braunstein, MD, Michael Shehata, MD, Xunzhang Wang, MD, Sumeet S. Chugh, MD

“…The positive and negative predictive values were 94.5% and 100.0%, respectively. …”
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Evaluation of low cryptococcal antigen titer as determined by the lateral flow assay in serum and cerebrospinal fluid among HIV-negative patients: a retrospective diagnostic accura... by Xuan Wang, Jia-Hui Cheng, Ling-Hong Zhou, Jun-Hao Zhu, Rui-Ying Wang, Hua-Zhen Zhao, Ying-Kui Jiang, Li-Ping Huang, Ching-Wan Yip, Chun-Xing Que, Min Zhu, Li-Ping Zhu

“…No false-positive cases were identified in patients with low CrAg titers in CSF and all positive predictive values (PPVs) were 100%. Among the cases with low serum CrAg titers, lumbar puncture was performed in 97 patients and positive CSF CrAg titers were reported in 6 patients. …”
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The Validation of an Artificial Intelligence-Based Software for the Detection and Numbering of Primary Teeth on Panoramic Radiographs by Heba H. Bakhsh, Dur Alomair, Nada Ahmed AlShehri, Alia U. Alturki, Eman Allam, Sara M. ElKhateeb

“…The AI’s performance was assessed by comparing its output to the ground truth using sensitivity, specificity, predictive values, accuracy, and the Kappa coefficient. …”
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Unveiling the pathogenic mechanisms of polyethylene terephthalate-microplastic-driven osteoarthritis and rheumatoid arthritis: PTGS2 signaling hub-oriented toxicity profiling by Jingkai Di, Shuang Wang, Lujia Liu, Keying Rong, Zijian Guo, Yingda Qin, Feida Wang, Chuan Xiang

“…After further screening, two proteins such as AKT1 and four proteins such as NR3C1 have relatively high predictive values in OA and RA respectively. Among them, PTGS2 and PET-MPs are strongly correlated targets causing injuries in OA and RA. …”
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Evaluation of AI-Powered Routine Screening of Clinically Acquired cMRIs for Incidental Intracranial Aneurysms by Christina Carina Schmidt, Robert Stahl, Franziska Mueller, Thomas David Fischer, Robert Forbrig, Christian Brem, Hakan Isik, Klaus Seelos, Niklas Thon, Sophia Stoecklein, Thomas Liebig, Johannes Rueckel

“…<b>Results</b>: The algorithm demonstrates high sensitivities (100% for findings >4 mm in diameter), a 17.8% MRA alert rate and positive predictive values of 11.5–43.8% (depending on whether inconclusive findings are considered or not). …”
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Application of prediction model based on CT radiomics in prognosis of patients with non-small cell lung cancer by Zefei Peng, Yubo Wang, Yurong Qi, Hao Hu, Yang Fu, Jiageng Li, Wei Li, Zhanxuan Li, Weilian Guo, Chunqi Shen, Jiezhi Jiang, Bin Yang

“…The calibration curve exhibited that the predicted values of the prognostic prediction model agreed well with the actual values. …”
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Application of non-invasive prenatal testing for fetal chromosomal disorders in low-risk pregnancies: a follow-up study in central China by Qiuxiang Huang, Qiuxiang Huang, Qiao Xu, Meihuan Chen, Meihuan Chen, Wenli Fan, Hailong Huang, Hailong Huang

“…A total of 572 (95.65%) patients with NIPT-positive results underwent amniocentesis, and 55.77% (319/572) cases were confirmed. The positive predictive values (PPV) for T21, T18, T13, SCAs, RAAs, and CNVs were 87.50%, 60.00%, 34.78%, 58.97%, 32.50%, and 69.70%, respectively, and the PPV for the trisomy was higher than that for the X-monomer in SCAs. …”
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Prospective observational study to assess the performance accuracy of clinical decision rules in children presenting to emergency departments with possible cervical spine injuries:... by Franz E Babl, Simon Craig, Susan M Donath, Meredith L Borland, Natalie Phillips, Amit Kochar, Gavin A Davis, Shane George, Stuart Dalziel, Arjun Rao, Nathan Kuppermann, Stacy Goergen, Sarah Watson, Amanda Williams, Eunicia Tan, Catherine L Wilson, Michelle Davison, Blessy John-Denny, Sonia Singh, Sharon O’Brien, Geoffrey N Askin, Chris J Selman, Julie C Leonard

“…The performance accuracy (sensitivity, specificity, negative and positive predictive values) of three existing CDRs in identifying children with study-defined CSIs and the specific CDR defined outcomes will be determined, along with multiple secondary outcomes including CSI epidemiology, investigations and management of possible CSI.Ethics and dissemination Ethics approval for the study was received from the Royal Children’s Hospital Melbourne Human Research Ethics Committee in Australia (HREC/69436/RCHM-2020) with additional approvals from the New Zealand Human and Disability Ethics Committee and the SingHealth Centralised Institutional Review Board. …”
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Utility of serum cytokine testing to differentiate complicated common variable immunodeficiency in resource limited settings by Aditi Jogdand, BS, Karen M. Gilbert, PhD, Joseph S. Hong, BS, Andrew J. Pak, BS, Katherine Liu, BA, Uhuru Kamau, MS, Neha V. Khairnar, MS, MBA, Henry C. Ssemaganda, MD, MS, Daniel DiGiacomo, MD, MPH, Sara Barmettler, MD, MPH, Mei-Sing Ong, PhD, Jocelyn R. Farmer, MD, PhD

“…We assessed the association of cytokine levels with AI disease and immunophenotypes using Wilcoxon test or Spearman correlation, statistically adjusted for multiple testing. We compared predictive values of cytokine levels and lymphocyte subsets, measured by the area under the receiver-operating characteristic curve. …”
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Optimising coronary imaging decisions with machine learning: an external validation study by Floor Groepenhoff, Leonard Hofstra, Sophie Heleen Bots, Saskia Haitjema, Imo Hoefer, L. Malin Overmars, Bram van Es, Mark C. H. De Groot, G. Aernout Somsen, I. Igor Tulevski, Hester M. den Ruijter, Wouter W. van Solinge

“…The outcome was defined as the absence of coronary stenosis, identified through text mining of radiology report conclusions, and predictive performance was assessed by negative predictive values (NPVs) and specificities.Results On the training cohort (9298 men (median age 55 years, 73% no coronary stenosis) and 5376 women (median age 59 years, 83% no coronary stenosis)), the algorithms showed NPVs and specificities of 0.95 and 0.14 in men and 0.93 and 0.26 in women, respectively. …”
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Optimization of chlorophyll extraction from mulberry leaves using response surface methodology by CHEN Shao-yuan, LÜ Zhen-er, DONG Feng-li, MAO Bi-zeng

“…Under the optimal extraction condition, the chlorophyll productivity was 5.376 mg/g, which was in consistent with the predicted value of 5.451 mg/g.In conclusion, the optimization of chlorophyll extraction by RSM is convenient, feasible and highly efficient.…”
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Validation of the arabic version of the edinburgh postnatal depression scale for screening antenatal depression in Oman by Khalood Al-abri, Hana AL Sumri, Mohammed Al-Azri, Divya Kuzhivilayil Yesodharan, Rahma Al Kindi

“…Results The Omani version validation of the EPDS yielded an optimal cut-off score of 11/12 for antenatal depression, with sensitivity, specificity, positive and negative predictive values of 86.30%, 71.37%, 45.65%, and 94.92%, and an area under the curve of 0.85. …”
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