CooccurrenceAffinity: An R package for computing a novel metric of affinity in co-occurrence data that corrects for pervasive errors in traditional indices. by Kumar P Mainali, Eric Slud

“…Analysis of co-occurrence data with traditional indices has led to many problems such as sensitivity of the indices to prevalence and the same value representing either a strong positive or strong negative association across different datasets. In our recent study (Mainali et al 2022), we revealed the source of the problems that make the traditional indices fundamentally flawed and unreliable-namely that the indices in common use have no target of estimation quantifying degree of association in the non-null case-and we further developed a novel parameter of association, alpha, with complete formulation of the null distribution for estimating the mechanism of affinity. …”
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Enhanced Learning Behaviors and Ability Knowledge Tracing by Fanglan Ma, Changsheng Zhu, Peng Lei, Peiwen Yuan

“…Specifically, on the longer sequence datasets ASSIST2012 and ASSISTChall, LBAKT achieved an AUC that is 8.8% higher than that of the worst-performing model, demonstrating superior performance. …”
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Comprehensive Analysis Reveals PTK6 as a Prognostic Biomarker Involved in the Immunosuppressive Microenvironment in Breast Cancer by Lili Wang, Shuimei Luo, Ziming Wang, Yiqiang Huang, Yang Luo, Xianhe Xie

“…However, its expression and the clinical importance it may have in patients with BC have not been explored. Based on datasets from the TCGA database and GTEx database, we studied the expressions and functions of PTK6 across 33 different kinds of cancer. …”
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Approaching maximum resolution in structured illumination microscopy via accurate noise modeling by Ayush Saurabh, Peter T. Brown, J. Shepard Bryan IV, Zachary R. Fox, Rory Kruithoff, Cristopher Thompson, Comert Kural, Douglas P. Shepherd, Steve Pressé

“…On the other hand, supervised algorithms rely on large datasets for training, and often require retraining for new sample structures. …”
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Single-cell landscape of dynamic changes in CD8+ T cells, CD4+ T cells and exhausted T cells in hepatocellular carcinoma by Rongqiang Liu, Jing Ye, Jianguo Wang, Wangbin Ma, Zhendong Qiu, Jia Yu, Weixing Wang

“…The results of the three independent datasets suggested that the model had strong prognostic value. …”
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Evaluating 28-Days Performance of Rice Husk Ash Green Concrete under Compression Gleaned from Neural Networks by Sharanjit Singh, Harish Chandra Arora, Aman Kumar, Nishant Raj Kapoor, Kennedy C. Onyelowe, Krishna Kumar, Hardeep Singh Rai

“…In this study, a total of 407 datasets are used to develop an ML-based model by using the ANN algorithm to predict the CS of concrete containing RHA. …”
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Machine Learning-Based Normal White Blood Cell Multi-Classification Optimization by Taeyeon Gil, Sukjun Lee, Onseok Lee

“…Therefore, in this study, we proposed an ML-based optimization system for five normal WBC classifications. Open datasets, Raabin-WBC, and private data were used. WBCs were segmented into nucleus, cytoplasm, and cell regions using U-Net, a DL model. …”
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Long-term health consequences and costs of changes in alcohol consumption in England during the COVID-19 pandemic. by Joshua Card-Gowers, Sadie Boniface, Jamie Brown, Loren Kock, Alexander Martin, Lise Retat, Laura Webber

“…Inputted data were obtained from the Alcohol Toolkit Study, and demographic, health and cost data from published literature and publicly available datasets. Three scenarios were modelled: short, medium, and long-term, where 2020 drinking patterns continue until the end of 2022, 2024, and 2035, respectively. …”
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Sensitivity and identifiability analysis of COVID-19 pandemic models by O. I. Krivorotko, S. I. Kabanikhin, M. I. Sosnovskaya, D. V. Andornaya

“…It has been demonstrated that a more general COVID-19 spread compartmental model consisting of seven ordinary differential equations describes the main trend of the spread and is sensitive to the peaks of conf irmed cases but does not qualitatively describe small statistical datasets such as the number of daily critical cases or mortality that can lead to errors in forecasting. …”
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Diagnosis-Based Hybridization of Multimedical Tests and Sociodemographic Characteristics of Autism Spectrum Disorder Using Artificial Intelligence and Machine Learning Techniques:... by M. E. Alqaysi, A. S. Albahri, Rula A. Hamid

“…Finally, this study critically reviews the literature and attempts to address the diagnosis ASD research gaps in knowledge and highlights the available ASD datasets, AI techniques and ML algorithms, and the feature selection methods that have been collected from the final set of articles.…”
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Influence of transient conditions on thermal comfort evaluations: Field study in university buildings by Keovathana Run, Franck Cévaër, Jean-François Dubé

“…To create transient-state and steady-state datasets, random groups of participants completed questionnaire surveys at various time points. …”
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Confidence-Aware Embedding for Knowledge Graph Entity Typing by Yu Zhao, Jiayue Hou, Zongjian Yu, Yun Zhang, Qing Li

“…The extensive experimental results in two public benchmark datasets (i.e., FB15kET and YAGO43kET) demonstrate that our proposed model outperforms all baselines on all tasks, which verify the effectiveness of ConfE in learning better embeddings on noisy KGs. …”
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FSErasing: Improving Face Recognition with Data Augmentation Using Face Parsing by Hiroya Kawai, Koichi Ito, Hwann-Tzong Chen, Takafumi Aoki

“…Through experiments using public face image datasets, we demonstrate that FSErasing is effective for improving the performance of face recognition and face attribute estimation. …”
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RNA modification writer-based immunological profile and genomic landscape of tumor microenvironment in lung adenocarcinoma by Qiang Xu, Lingyu Kong, Zhezhu Han, Xiuying Jin, Mingyan Ding, Zhengri Piao, Songnan Zhang

“…Methods We assessed the expression properties and genetic alterations of 26 RNA modification writers, including adenosine-to-inosine RNA editing, alternative polyadenylation, m1A, and m6A in 502 lung adenocarcinoma (LUAD) samples from the Cancer Genome Atlas (TCGA) datasets. Then, we used differentially expressed gene (DEGs) to develop a signature for predicting patient outcomes, which was dubbed the “writer score” for RNA-modified writers. …”
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The co-occurrence of multimorbidity and polypharmacy among middle-aged and older adults in Canada: A cross-sectional study using the Canadian Longitudinal Study on Aging (CLSA) and... by Kathryn Nicholson, Jennifer Salerno, Sayem Borhan, Benoit Cossette, Dale Guenter, Meredith Vanstone, John Queenan, Michelle Greiver, Michelle Howard, Amanda L Terry, Tyler Williamson, Lauren E Griffith, Martin Fortin, Saverio Stranges, Dee Mangin

“…<h4>Methods and findings</h4>This study reported on multimorbidity and polypharmacy among middle-aged and older adults in two national datasets: the Canadian Longitudinal Study on Aging (CLSA) and the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). …”
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Random Cross-Validation Produces Biased Assessment of Machine Learning Performance in Regional Landslide Susceptibility Prediction by Chandan Kumar, Gabriel Walton, Paul Santi, Carlos Luza

“…., it ignores the spatial autocorrelation (SAC) inherent in spatial datasets when partitioning the training and testing sets. …”
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Out-of-distribution generalization for segmentation of lymph node metastasis in breast cancer by Yiannis Varnava, Kiran Jakate, Richard Garnett, Dimitrios Androutsos, Pascal N. Tyrrell, April Khademi

“…This work proposes a novel clustering and sampling method to automatically curate training datasets in an unsupervised manner with the aim of improving model generalization abilities. …”
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Towards the Measurement of Sea-Ice Thickness Using a Time-Domain Inductive Measurement System by Danny Hills, Becan Lawless, Rauan Khangerey, Jeremy Wilkinson, Liam A. Marsh

“…The measured and simulated datasets are presented along with a proposed form of post-processing, which establishes a correlation between the distance to the sea surface and the measured EMI response. …”
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Prognosis Analysis and Validation of Fatty Acid Metabolism-Related lncRNAs and Tumor Immune Microenvironment in Cervical Cancer by Xiaolin Lang, Changchang Huang, Hongyin Cui

“…FAM-related differentially expressed genes (DEGs) and lncRNAs were screened in CC specimens based on TCGA datasets. Univariate analysis was carried out on differentially expressed lncRNAs to screen the survival-related lncRNAs. …”
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A Spatial&#x2013;Temporal Difference Aggregation Network for Gaofen-2 Multitemporal Image in Cropland Change Area by Chuang Liu, Liyang Bao, Zhiqi Zhang

“…In addition, we conduct generalization experiments on the remaining three mainstream datasets, demonstrating that our method is equally applicable to other change detection scenarios.…”
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