Is the convergence insufficiency symptom survey applicable to elderly individuals? by Saeid Abdi, Haleh Kangari, Saeed Rahmani, Alireza Akbarzadeh Baghban, Zahra Kamary Rad

“…The mean CISS scores for presbyopes with CI and normal groups were 19.24 ± 5.33 and 13.26 ± 3.53 respectively (p < 0.001). Effective discrimination was achieved with a score greater than 15, yielding a sensitivity of 72%, a specificity of 69%, and an Area Under the Curve (AUC) of 0.813. …”
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Development and assessment of a mortality risk prediction nomogram model for pneumocystis disease in ICU within 28 days by Yiru Weng, Tingting Zhou, Honghua Ye

“…Demonstrating robust discrimination and calibration, this tool provides clinicians with a valuable resource for assessing prognosis and making evidence-based treatment decisions.…”
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Developing a youth-friendly internet-enabled HIV risk calculator: A collaborative approach with young key populations, living in Soweto, South Africa. by Mamakiri Mulaudzi, Gugulethu Tshabalala, Stefanie Hornschuh, Kofi Ebenezer Okyere-Dede, Minjue Wu, Oluwatobi Ifeloluwa Ariyo, Janan J Dietrich

“…LGBT individuals are identified as key populations because they face increased vulnerability to HIV/AIDS and other health risks due to societal stigma, discrimination, and obstacles in accessing healthcare and support services. …”
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Développement d’un marqueur moléculaire pour l’identification des lamproies au stade juvénile by Ahmed SOUISSI, Anne-Laure BESNARD, Guillaume EVANNO

“…En particulier, la lamproie de Planer et la lamproie de rivière étant impossibles à distinguer morphologiquement au stade juvénile, ce projet a permis de développer un outil moléculaire de discrimination de ces deux espèces. Ainsi, il est désormais possible d’identifier l’espèce à partir d’un morceau de nageoire prélevé de manière non létale sur une larve (dite « ammocète ») collectée sur le terrain. …”
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Prediction of Length of Stay After Colorectal Surgery Using Intraoperative Risk Factors by Daitlin Esmee Huisman, MD, Erik Wouter Ingwersen, MD, Joanna Luttikhold, MD, PhD, Gerrit Dirk Slooter, MD, PhD, Geert Kazemier, MD, PhD, Freek Daams, MD, PhD, LekCheck Study Group, Audrey Jongen, Carlo V. Feo, Simone Targa, Hidde M. Kroon, Emmanuel A. G. L. Lagae, Aalbert K. Talsma, Johannes A. Wegdam, Bob van Wely, Dirk J. A. Sonneveld, Sanne C. Veltkamp, Emiel G. G. Verdaasdonk, Rudi M. H. Roumen, Freek Daams

“…The difference in discrimination between the 2 models was statistically significant (DeLong test, P < 0.001). …”
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Development and validation of the Japanese version of the Public Attitudes Toward Epilepsy (PATE‐J) Scale by Junichi Hatakeda, Hiroumi Shimazaki, Izumi Kuramochi, Takayuki Iwayama, Sayaka Kobayashi, Hideyuki Matsuki, Haruo Yoshimasu, Kheng Seang Lim

“…Internal consistency assessment, and convergent validity testing with the Modified Epilepsy Stigma Scale (M‐ESS), Perceived Devaluation Discrimination Scale (PDDS), and Epilepsy Knowledge Scale (EKS) were carried out. …”
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Construction of nomogram model based on contrast-enhanced ultrasound parameters to predict the degree of pathological differentiation of hepatocellular carcinoma by Shu-Min Lian, Hong-Jing Cheng, Hong-Jing Li, Hui Wang

“…The patients were randomly divided into training set and testing set in a ratio of 7:3, in which the parameters of the training set were analyzed by univariate analysis and then stepwise regression to construct the prediction model, and the diagnostic efficacy of the validation model was evaluated by discrimination, calibration, and clinical applicability.ResultsA total of 189 patients with primary hepatocellular carcinoma were enrolled, including 118 patients in the low-grade group and 71 patients in the high-grade group; they were randomly divided into training set of 128 patients and testing set of 61 patients. …”
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Construction of machine learning-based models for screening the high-risk patients with gastric precancerous lesions by Shuxian Yu, Haiyang Jiang, Jing Xia, Jie Gu, Mengting Chen, Yan Wang, Xiaohong Zhao, Zehua Liao, Puhua Zeng, Tian Xie, Xinbing Sui

“…Abstract Background The individualized prediction and discrimination of precancerous lesions of gastric cancer (PLGC) is critical for the early prevention of gastric cancer (GC). …”
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A Simple Nomogram for Predicting the Development of ARDS in Postoperative Patients with Gastrointestinal Perforation: A Single-Center Retrospective Study by Zhang Z, Zhao H, Zhang Z, Jia L, Long L, Fu Y, Du Q

“…Nomograms were developed to show predictive models, and the discrimination, calibration, and clinical usefulness of the models were assessed using the C-index, calibration plots, and decision curve analysis (DCA).Results: Two hundred patients were ultimately included for analysis. …”
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Understanding the Origin of SSR in Series-Compensated DFIG-Based Wind Farms: Analysis Techniques and Tuning by Roberto Moreno-Sanchez, C. Alberto Nunez-Gutierrez, Nancy Visairo-Cruz, Julio Hernandez-Ramirez, Juan Segundo-Ramirez

“…As a result, the modes involved in the SSR phenomenon are identified and a discrimination procedure is described to determine the origin of the SSR.…”
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Risk factors analysis and prediction model establishment of acute kidney injury after heart valve replacement in patients with normal renal function by Xiaofan Huang, Xiaofan Huang, Xiangyu Sun, Jiangang Song, Yongqiang Wang, Jindong Liu, Jindong Liu, Yu Zhang, Yu Zhang

“…The calibration curve slope was close to 1, and the DCA showed that the model produced better clinical benefits when the probability threshold was set at 10%–82%.ConclusionsWe developed a preoperative risk prediction model for AKI after heart valve replacement in patients with normal renal function, which demonstrated satisfactory discrimination and calibration.…”
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The role of light and vision in farmed ungulates and implications for their welfare by Julia Stuhlträger, Eberhard von Borell, Jan Langbein, Christian Nawroth, Maria Vilain Rørvang, Camille M. C. Raoult, Camille M. C. Raoult

“…From a human perspective, we tend to overestimate the importance of color perception and preference, whereas contrast discrimination in combination with illumination intensity and quality seems to be more relevant for ungulate orientation and interaction with their environment. …”
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Risk prediction models for falls in hospitalized older patients: a systematic review and meta-analysis by Anli Mao, Jie Su, Mingzhu Ren, Shuying Chen, Huafang Zhang

“…Eight models reported discrimination metrics and two models reported calibration metrics. …”
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A Study on Multi-Scale Behavior Recognition of Dairy Cows in Complex Background Based on Improved YOLOv5 by Zheying Zong, Zeyu Ban, Chunguang Wang, Shuai Wang, Wenbo Yuan, Chunhui Zhang, Lide Su, Ze Yuan

“…Moreover, it outperformed comparison models, including YOLOv4, YOLOv3, and Faster R-CNN, in complex background scenarios, multi-scale behavior detection, and behavior type discrimination. Ablation experiments further validate the effectiveness of the SA, DCNv3, and DyHead modules. …”
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Predicting complications of major head and neck oncological surgery: an evaluation of the ACS NSQIP surgical risk calculator by Peter S. Vosler, Mario Orsini, Danny J. Enepekides, Kevin M. Higgins

“…Analyses by procedure were excellent, with the risk calculator showing adequate calibration for 7 of 8 procedural categories and adequate discrimination for all calculable categories (6 of 6). …”
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Chemical Fingerprint Analysis for Discovering Markers and Identifying Saussurea involucrata by HPLC Coupled with OPLS-DA by Qingdong Ma, Xiaoxiang Chen, Ke Zhang, Dahong Yao, Lu Yang, Hangyu Wang, Santai Bulemasi, Jian Huang, Jinhui Wang

“…In addition, different haplotypes of S. involucrata can be discriminated in the OPLS-DA model using the 20 common peaks. …”
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Development and validation of a prediction model for all-cause mortality in maintenance dialysis patients: a multicenter retrospective cohort study by Jingcan Wu, Xuehong Li, Hong Zhang, Lin Lin, Man Li, Gangyi Chen, Cheng Wang

“…Variables were selected by LASSO-Cox regression, and the model was constructed by Cox regression, which was presented in the form of nomogram and web-based tool. The discrimination and accuracy of the prediction model were assessed using C-indexes and calibration curves, while the clinical value was assessed by decision curve analysis (DCA).Results The best predictors of 1-, 3-, and 5-year all-cause mortality contained nine independent factors, including age, body mass index (BMI), diabetes mellitus (DM), cardiovascular disease (CVD), cancer, urine volume, hemoglobin (HGB), albumin (ALB), and pleural effusion (PE). …”
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Genetic diversity of potato varieties bred in Russia and near-abroad countries based on polymorphism of SSR-loci and markers associated with resistance R-genes by O. Y. Antonova, N. A. Shvachko, L. Y. Novikova, O. Y. Shuvalov, L. I. Kostina, N. S. Klimenko, A. R. Shuvalova, T. A. Gavrilenko

“…Application of 14 highly polymorphic nuclear microsatellites (SSR) enabled the complete discrimination of all 113 varieties. Additionally, we have studied these varieties for the distribution of 8 DNA markers associated with three R-genes involved in the control of resistance to two quarantine objects: the potato wart Synchytrium endobioticum and golden potato cyst nematode Globodera rostochiensis, which occur locally in some regions of the Russian Federation. …”
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اعادة الهندسة الاداریة کمدخل لتمیز مؤسسات المعرفة by د. أمنیة خیر توفیق

“…Different types of knowledgeinstitutions need to re-engineer management , whether they suffer or not fromproblems of re-engineering in knowledge institutions : Service of reengineering ,reengineering process , reengineering ofmanagement systems , reengineering requires management improvementand development especially in the areas of organizational work , process outputs, system , and resources .A set of reengineering approaches that can be reliably applied toknowledge institutions is available from the results of the application of thereengineering approach to knowledge institutions : the transformation ofbusiness units from functional departments to operations teams , transformingjobs from simple tasks to complex work , the focus shifts on performancestandards , rewards and activities to results , Examples of obstacles that arepreventing the re-engineering approach to knowledge. institutions : the existenceof a culture of resistance to change, the lack of clarity of the knowledge        institution's vision , its organizational culture in the process of re-engineering, theuse of non-cadres to lead the process of administrative re-engineering, assigningadministrative re-engineering to retiring individuals , non-discrimination betweenadministrative re-engineering and other change programs, An example of therequirements for : The adequate awareness of the wishes of the beneficiaries ,an analysis of the institution's position and the design of the objectives of change, the belief of the senior management in the importance of change andencouragement of employees and understanding of the process of reengineeringadministrative management .Recommendations of the study : The need to adopt conscious leaders indifferent types of knowledge institutions , providing the necessary budget forapplying administrative reengineering in knowledge institutions , establishing aspecialized unit for reengineering of knowledge institutions , setting a plan for aspecific period of time of different types , especially the leaders in which newskills and knowledge on the reengineering management , monitoring theexperiences and management practices distinct in the field of reengineeringmanagement services facilities to document and benefit from them , increasingdependence needed to support administrative processes of reengineeringmethod of information technology .…”
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Artificial intelligence assisted risk prediction in organ transplantation: a UK Live-Donor Kidney Transplant Outcome Prediction tool by Hatem Ali, Arun Shroff, Tibor Fülöp, Miklos Z. Molnar, Adnan Sharif, Bernard Burke, Sunil Shroff, David Briggs, Nithya Krishnan

“…Introduction: Predicting the outcome of a kidney transplant involving a living donor advances donor decision-making donors for clinicians and patients. However, the discriminative or calibration capacity of the currently employed models are limited. …”
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