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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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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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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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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Large-Scale Topographic Mapping Using RTK-GNSS and Multispectral UAV Drone Photogrammetric Surveys: Comparative Evaluation of Experimental Results by Siyandza M. Dlamini, Yashon O. Ouma

“…Geometrically, the average difference in the perimeter and areas of the features from the RTK-GNSS and UAV drone topographical maps were −0.26% and −0.23%, respectively. …”
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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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Data popularity-based encrypted deduplication scheme without third-party servers by Guanxiong HA, Qiaowen JIA, Hang CHEN, Chunfu JIA

“…It is effective to balance data security and storage efficiency for setting different levels of security protection for data based on popularity in encrypted deduplication systems.Existing schemes all need introduce a trusted third-party for recording data popularity, while the third party is prone to a single point of failure and efficiency bottleneck.To address this problem, a popularity-based encrypted deduplication scheme without third-party servers was proposed, which accurately recorded the data popularity based on the Count-Min sketch algorithm and Merkle Puzzles protocol, and achieved encrypted deduplication of unpopular data through the sPAKE protocols performed among users.Security analysis and experimental evaluation show that the proposed scheme is secure and efficient.…”
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Development and validation of a model to identify polycystic ovary syndrome in the French national administrative health database by Eugénie Micolon, Sandrine Loubiere, Appoline Zimmermann, Julie Berbis, Pascal Auquier, Blandine Courbiere

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Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups by Ebtisam AlJalaud, Manar Hosny

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Heuristic based federated learning with adaptive hyperparameter tuning for households energy prediction by Liana Toderean, Mihai Daian, Tudor Cioara, Ionut Anghel, Vasilis Michalakopoulos, Efstathios Sarantinopoulos, Elissaios Sarmas

“…The federated model aggregation is optimized using hierarchical simulated annealing optimization to prioritize updates from the better-performing models. A genetic algorithm-based hyperparameter optimization method reduces the computational load on edge nodes by efficiently exploring different configurations and using only the most promising ones for edge nodes’ cross-validation. …”
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Statistical Evaluation of Smartphone-Based Automated Grading System for Ocular Redness Associated with Dry Eye Disease and Implications for Clinical Trials by Rodriguez JD, Hamm A, Bensinger E, Kerti SJ, Gomes PJ, Ousler III GW, Gupta P, De Moraes CG, Abelson MB

“…The model utilizes the DeepLabV3 architecture for image segmentation, extracting two key features—horizontality and redness. The algorithm then uses these features to predict eye redness, validated by comparison with expert grader scores.Results: The bivariate model using both redness and horizontality performed best, with a Mean Absolute Error (MAE) of 0.450 points (SD=0.334) on the redness scale relative to expert scores. …”
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Educational Technologies in Modern Higher Education Institutions (Analysis of Russian and Foreign Research and Practice) by N. V. Bordovskaia, E. A. Koshkina, N. A. Bochkina

“…It has been established that Russian authors are still more oriented towards describing the characteristics and algorithms of predominantly traditional educational technologies and their applicability, evaluating their effectiveness through influencing students’ professional and personal development and competent communication. …”
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Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study. by Stephanie Archer, Chantal Babb de Villiers, Fiona Scheibl, Tim Carver, Simon Hartley, Andrew Lee, Alex P Cunningham, Douglas F Easton, Jennifer G McIntosh, Jon Emery, Marc Tischkowitz, Antonis C Antoniou, Fiona M Walter

“…<h4>Background</h4>There is a growing focus on the development of multi-factorial cancer risk prediction algorithms alongside tools that operationalise them for clinical use. …”
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Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production by Kristen L. Beck, Niina Haiminen, Akshay Agarwal, Anna Paola Carrieri, Matthew Madgwick, Jennifer Kelly, Victor Pylro, Ban Kawas, Martin Wiedmann, Erika Ganda

“…The objective of this study was to assess the feasibility of using shotgun sequencing data as input into anomaly detection algorithms using fluid milk as a model system. Contrastive principal component analysis (PCA), cluster-based methods, and explainable artificial intelligence (AI) were evaluated for the detection of two anomalous sample classes using longitudinal metagenomic profiling of fluid milk compared to baseline (BL) samples collected under comparable circumstances. …”
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Evaluation of the Effectiveness of Pulsed Ultraviolet Devices in Medical Premises of the Emergency Department of a Hospital Under Conditions of Intensive Patient Flow by B. L. Kurilin, N. E. Drozdova, A. Yu. Perminov, E. V. Kislukhina, Ya. V. Kulikova, N. S. Fomenko, A. V. Shapoval, V. I. Drozdova, A. R. Samarin

“…Preventive disinfection of work surfaces was carried out after each patient by wiping with the use of approved products.The experimental premises were treated according to a single standard algorithm, including treatment with the Installation.To collect microbiological swabs, sampling points were defined in the studied premises (4 in each). …”
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Research on prediction of bottom hole flowing pressure for vertical coalbed methane wells based on improved SSA-BPNN by YU Yang, DONG Yintao, LI Yunbo, BAO Yu, ZHANG Lixia, SUN Hao

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BLACK HUMOUR: ORIGIN DESCRIPTION AND AN ATTEMPT OF IDENTIFICATION by Iryna A. Blynova.

“…Typical means at the syntactic level are overinterrogations and explanations based on repetitions with an evaluation of what was heard. This evaluation is expressed by declarative, exclamatory or interrogative sentences. …”
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Overcoming negative weighting in uncertainty-based methods: a multi-uncertainty clustering method for evidence fusion by Zhike Qiu, Yuhao Qin, Zichong Chen, Luping Zeng, Rui Cai

“…Furthermore, this research designs a composite weight that combines cluster weight with similarity weight, providing a comprehensive evaluation of evidence reliability from both macro-level category differences and micro-level similarity dimensions. …”
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