An extension of the Spiegelhalter-Knill-Jones method for continuous covariates in clinical decision making by Bart K. M. Jacobs, Tafadzwa Maseko, Lutgarde Lynen, Aquiles Rodrigo Henriquez-Trujillo, Jozefien Buyze

“…Abstract Background There is still demand for algorithms that can be used at the point of care, especially when dealing with events that do not present with a single obvious clinical indicator. …”
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“Clinical Stability” and Propensity Score Matching in Cardiac Surgery: is the clinical evaluation of treatment efficacy algorithmdependent in small sample size settings? by Daniele Bottigliengo, Aslıhan Sentürk Acar, Veronica Sciannameo, Giulia Lorenzoni, Jonida Bejko, Tomaso Bottio, Emanuele Cozzi, Marta Vadori, Jean-Paul Soulillou, Thierry Le Torneau, Thomas Senage, Rafael Mañez, Cristina Costa, Vered Padler-Karavani, Sofia Scali, Massimiliano Carrozzini, Emilia Fiorello, Samuel Fusca, Gino Gerosa, Ileana Baldi, Paola Berchialla, Dario Gregori

“…Differences between subjects in the matched sets were evaluated by comparing both pre-treatment covariates and propensity score distributions. …”
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Research on optimal scheduling of minor and moderate floods for cascade reservoirs in the lower reaches of the jinsha river considering power generation by Zaimin Ren, Bin He, Chenchen Yao, Xiaoshuai Lv, Xihong Wang

“…An evaluation index system was developed to select optimal solutions under different flood frequencies, using the Minimum Discriminant Information Principle and VIKOR model. …”
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Local Sub-Block Contrast and Spatial–Spectral Gradient Feature Fusion for Hyperspectral Anomaly Detection by Dong Zhao, Xingchen Xu, Mingtao You, Pattathal V. Arun, Zhe Zhao, Jiahong Ren, Li Wu, Huixin Zhou

“…Most existing hyperspectral anomaly detection algorithms primarily rely on spatial information to identify anomalous targets. …”
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“Clinical Stability” and Propensity Score Matching in Cardiac Surgery: is the clinical evaluation of treatment efficacy algorithmdependent in small sample size settings? by Daniele Bottigliengo, Aslıhan Sentürk Acar, Veronica Sciannameo, Giulia Lorenzoni, Jonida Bejko, Tomaso Bottio, Emanuele Cozzi, Marta Vadori, Jean-Paul Soulillou, Jean Christian Roussel, Thierry Le Torneau, Thomas Senage, Rafael Mañez, Cristina Costa, Vered Padler-Karavani, Sofia Scali, Massimiliano Carrozzini, Emilia Fiorello, Samuel Fusca, Gino Gerosa, Ileana Baldi, Paola Berchialla, Dario Gregori

“…Differences between subjects in the matched sets were evaluated by comparing both pre-treatment covariates and propensity score distributions. …”
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Optimization-Based Downscaling of Satellite-Derived Isotropic Broadband Albedo to High Resolution by Niko Lukač, Domen Mongus, Marko Bizjak

“…Next, the Differential Evolution (DE) optimization algorithm is applied to approximate albedo values to these segments so that their spatial aggregate matches the coarse-resolution satellite albedo, by proposing two novel objective functions. …”
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The study of thermodynamic mechanisms of advection-cooled sea fogs for two cases based on the WRF model by Xin-Ya Ye, Fei-Fei Shen, Fei-Fei Shen, Fei-Fei Shen, Hai-Yan Fei, Qi-Long Sun, Ai-Qing Shu, Shen Wan, He Chen

“…In terms of fog prediction, the FSL algorithm outperformed SW99 in estimating fog coverage, although both had limitations in accurately predicting visibility levels.DiscussionThis comparative analysis highlights the influence of differing synoptic and mesoscale conditions on the formation and evolution of advection-cooled sea fog. …”
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An Industrial Internet Security Assessment Model Based on a Selectable Confidence Rule Base by Qingqing Yang, Shiming Li, Yuhe Wang, Guoxing Li, Yanbin Yuan

“…Finally, the experiments of different evaluation models on industrial data sets are compared, and good results are obtained, which verify the evaluation accuracy of the industrial Internet network security situation assessment model proposed in this paper and the feasibility and effectiveness of the S-CMA-ES optimization algorithm.…”
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Accuracy evaluation of dental CBCT and scanned model registration method based on pulp horn mapping surface: an in vitro proof-of-concept by Dianhao Wu, Jingang Jiang, Jinke Wang, Shan Zhou, Kun Qian

“…Then, in the C +  + programming environment with a point cloud library (PCL), the PHMSR, the traditional sparse ICP, ICP, and coherent point drift (CPD) algorithms are used to register the point clouds under two different initial deviations. …”
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SIGNAL AS A TOOL OF THE PHARMACOVIGILANCE by E. O. Zhuravleva, N. Yu. Velts, G. V. Kutekhova, M. A. Darmostukova, R. N. Alyautdin

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Drone-Based Digital Phenotyping to Evaluating Relative Maturity, Stand Count, and Plant Height in Dry Beans (Phaseolus vulgaris L.) by Leonardo Volpato, Evan M. Wright, Francisco E. Gomez

“…For early-stage SC assessment, Faster RCNN object detection algorithm was evaluated. Flight frequencies, image resolution, and data augmentation techniques were investigated to enhance DL model performance. …”
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Network security threat warning method based on qualitative differential game by Shirui HUANG, Hengwei ZHANG, Jindong WANG, Ruiyu DOU

“…Most current network security research based on game theory adopts the static game or multi-stage dynamic game model,which does not accord with the real-time change and continuity of the actual network attack-defense process.To make security threats warning more consistent with the attack-defense process,the threat propagation process was analyzed referring to the epidemic model.Then the network attack-defense game model was constructed based on the qualitative differential game theory,by which the evolution of the network security state could be predicted.Based on the model,the qualitative differential game solution method was designed to construct the attack-defense barrier and divide the capture area.Furthermore,the threat severity in different security states were evaluated by introducing multidimensional Euclidean distance.By designing the warning algorithm,the dynamic warning of the network security threat was realized,which had better accuracy and timeliness.Finally,simulation results verify the effectiveness of the proposed algorithm and model.…”
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Semi-automated evaluation of trabecular meshwork and schlemm canal imaged with OCT in children with normal eyes vs. primary congenital glaucoma by Bo Wang, Alden P. Gregston, Rizul Naithani, Samuel Alvarez, Rohini R. Sigireddi, Sharon F. Freedman

“…Abstract Maldevelopment of Schlemm canal (SC) and trabecular meshwork (TM) is proposed in the pathogenesis of primary congenital glaucoma (PCG). This study aims to evaluate a semi-automated segmentation algorithm of SC and TM in pediatric patients scanned using overhead-mounted optical coherence tomography (OCT). …”
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The CURE Protocol: evaluation and external validation of a new public health strategy for treating paediatric hydrocephalus in low-resource settings by Benjamin C Warf, Stephanie H Chen, Jacob R Lepard, Michael C Dewan, Olufemi B Bankole, John Mugamba, Peter Ssenyonga, Abhaya V Kulkarni

“…Introduction Managing paediatric hydrocephalus with shunt placement is especially risky in resource-limited settings due to risks of infection and delayed life-threatening shunt obstruction. This study evaluated a new evidence-based treatment algorithm to reduce shunt-dependence in this context.Methods A prospective cohort design was used. …”
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Building the Future of Transportation: A Comprehensive Survey on AV Perception, Localization, and Mapping by Ashok Kumar Patil, Bhargav Punugupati, Himanshi Gupta, Niranjan S. Mayur, Srivatsa Ramesh, Prasad B. Honnavalli

“…Additionally, we present insights from our testing, evaluating the effectiveness of different perception, localization, and mapping methods in real-world conditions. …”
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Design and Experimental Study of Electrical Impedance Tomography System for Tumor Ablation Boundary Monitoring by Wei WEI, Lidong XING, Xiaofei JIN, Zhiyu QIAN, Jingqi SONG, Kairan WAN, Haotian WANG

“…The minimally invasive thermal ablation technology differs from traditional surgical operations, which requires auxiliary equipment to evaluate ablation results. …”
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An association rule-based approach for frequent item mining of multi-stage access data by Silong Wu

“…Only one database scan is required, and frequent itemsets are directly generated without generating candidate itemsets, greatly improving the efficiency of the algorithm; Introducing weights into the improved Apriori algorithm and designing a weighted support function, by assigning different weights to different itemsets, more accurately reflects the importance and differences of itemsets in practical applications, thereby improving the accuracy of frequent item mining. …”
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Joining forces for pathology diagnostics with AI assistance: The EMPAIA initiative by Norman Zerbe, Lars Ole Schwen, Christian Geißler, Katja Wiesemann, Tom Bisson, Peter Boor, Rita Carvalho, Michael Franz, Christoph Jansen, Tim-Rasmus Kiehl, Björn Lindequist, Nora Charlotte Pohlan, Sarah Schmell, Klaus Strohmenger, Falk Zakrzewski, Markus Plass, Michael Takla, Tobias Küster, André Homeyer, Peter Hufnagl

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Multilayer neural network model for unbalanced data by Xue ZHANG, Zhiguo SHI, Xuan LIU

“…Classification of unbalanced data often has low performance of the classifier because of the unbalance of data between classes.Using AUC (the area under the ROC curve) as evaluation index,combined with one class F-score feature selection and genetic algorithm,a multilayer neural network model was established,and a more favorable feature set for unbalanced data classification was selected,so as to establish a deeper model suitable for classification of unbalanced data.Based on Tensor Flow,a multilayer neural network model was established.Using four different UCI datasets for testing,and comparing with the traditional machine learning algorithms such as Naive Bayesian,KNN,neural networks,etc,the performance of the proposed model built on the unbalanced data classification is more excellent.…”
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Multilayer neural network model for unbalanced data by Xue ZHANG, Zhiguo SHI, Xuan LIU

“…Classification of unbalanced data often has low performance of the classifier because of the unbalance of data between classes.Using AUC (the area under the ROC curve) as evaluation index,combined with one class F-score feature selection and genetic algorithm,a multilayer neural network model was established,and a more favorable feature set for unbalanced data classification was selected,so as to establish a deeper model suitable for classification of unbalanced data.Based on Tensor Flow,a multilayer neural network model was established.Using four different UCI datasets for testing,and comparing with the traditional machine learning algorithms such as Naive Bayesian,KNN,neural networks,etc,the performance of the proposed model built on the unbalanced data classification is more excellent.…”
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