Table 1.
Articles in the COVOD-19 Special Issue.
| Reference | Title | First Author | Type of Article |
|---|---|---|---|
| Commentary and review (5) | |||
| [3] | Epistemic responsibilities in the COVID-19 pandemic: Is a digital infosphere a friend or a foe? | Curkovic, M. | Commentary |
| [4] | Mind the Clinical-Analytic Gap: Electronic Health Records and COVID-19 Pandemic Response | Sudat,S.E.K. | Commentary |
| [5] | Repurposing biomedical informaticians for COVID-19 | Sosa, D. N. | Commentary |
| [6] | Can technological advancements help to alleviate COVID-19 pandemic? a review | Thomas, M. J. | Methodological Review |
| [7] | Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance | Shahid, O. | Methodological Review |
| Clinical research and practice (13) | |||
| [8] | Making science computable: Developing code systems for statistics, study design, and risk of bias | Alper, B. S. | Special Communication |
| [9] | Obtaining EHR-derived datasets for COVID-19 research within a short time: a flexible methodology based on Detailed Clinical Models | Pedrera-Jimenez, M. | Original Research |
| [10] | Developing a sampling method and preliminary taxonomy for classifying COVID-19 public health guidance for healthcare organizations and the general public | Taber, P. | Original Research |
| [11] | Visual comprehension and orientation into the COVID-19 CIDO ontology | Zheng, L. | Original Research |
| [12] | Phenotyping coronavirus disease 2019 during a global health pandemic: Lessons learned from the characterization of an early cohort | DeLozier, S. | Special Communication |
| [13] | Extracting COVID-19 diagnoses and symptoms from clinical text: A new annotated corpus and neural event extraction framework | Lybarger, K. | Original Research |
| [14] | ELII: A novel inverted index for fast temporal query, with application to a large Covid-19 EHR dataset | Huang, Y. | Original Research |
| [15] | Creating and implementing a COVID-19 recruitment Data Mart | Helmer, T. T. | Special Communication |
| [16] | Critical carE Database for Advanced Research (CEDAR): An automated method to support intensive care units with electronic health record data | Schenck, E. J. | Special Communication |
| [17] | ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes | Zhao, J. | Special Communication |
| [18] | A retrospective approach to evaluating potential adverse outcomes associated with delay of procedures for cardiovascular and cancer-related diagnoses in the context of COVID-19 | Zheng, N. S. | Original Research |
| [19] | Learning from past respiratory failure patients to triage COVID-19 patient ventilator needs: A multi-institutional study | Carmichael, H. | Special Communication |
| [20] | A predictive model of clinical deterioration among hospitalized COVID-19 patients by harnessing hospital course trajectories | Mauer, E. | Original Research |
| Forecasting and epidemic modelling (9) | |||
| [21] | Implementation of stacking based ARIMA model for prediction of Covid-19 cases in India | Swaraj, A. | Original Research |
| [22] | A fusion of data science and feed-forward neural network-based modelling of COVID-19 outbreak forecasting in IRAQ | Aljaaf, A. J. | Original Research |
| [23] | Comparative study of machine learning methods for COVID-19 transmission forecasting | Dairi, A. | Original Research |
| [24] | A novel deep interval type-2 fuzzy LSTM (DIT2FLSTM) model applied to COVID-19 pandemic time-series prediction | Safari, A. | Original Research |
| [25] | COVID-19 modelling by time-varying transmission rate associated with mobility trend of driving via Apple Maps | JING, M. | Original Research |
| [26] | EPIsembleVis: A geo-visual analysis and comparison of the prediction ensembles of multiple COVID-19 models | Xu, H. | Special Communication |
| [27] | Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates | Huang T. | Original Research |
| [28] | An integrated framework for modelling quantitative effects of entry restrictions and travel quarantine on importation risk of COVID-19 | Chen, T. | Original Research |
| [29] | Dynamic graph and polynomial chaos based models for contact tracing data analysis and optimal testing prescription | Ubaru, S. | Original Research |
| Text mining of literature, social media, and trial documents (7) | |||
| [30] | Searching for scientific evidence in a pandemic: An overview of TREC-COVID | Roberts, K. | Special Communication |
| [31] | A comparative analysis of system features used in the TREC-COVID information retrieval challenge | Chen, J. | Original Research |
| [32] | Drug repurposing for COVID-19 via knowledge graph completion | Zhang, R. | Original Research |
| [33] | Pulse of the pandemic: Iterative topic filtering for clinical information extraction from social media | Wu, J. | Original Research |
| [34] | Defining facets of social distancing during the COVID-19 pandemic: Twitter analysis | Kwon, J. | Original Research |
| [35] | Tracking and analysis of discourse dynamics and polarity during the early Corona pandemic in Iran | Jafarinejad, F. | Special Communication |
| [36] | Building an OMOP common data model-compliant annotated corpus for COVID-19 clinical trials | Sun, Y. | Original Research |
| Translational bioinformatics (4) | |||
| [37] | A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19 | Das, J. K. | Original Research |
| [38] | Causal discovery using compression-complexity measures | Sy, P. | Original Research |
| [39] | Machine learning enabled identification of potential SARS-CoV-2 3CLpro inhibitors based on fixed molecular fingerprints and Graph-CNN neural representations | Haneczok, J. | Special Communication |
| [40] | Reservoir hosts prediction for COVID-19 by hybrid transfer learning model | Yang, Y. | Original Research |
| Others (7) | |||
| [41] | Dynamic deformable attention network (DDANet) for COVID-19 lesions semantic segmentation | Rajamani, K. T. | Original Research |
| [42] | An aberration detection-based approach for sentinel syndromic surveillance of COVID-19 and other novel influenza-like illnesses | Wen, A. | Original Research |
| [43] | IoT-based GPS assisted surveillance system with inter-WBAN geographic routing for pandemic situations | Savasci Sen, S. | Special Communication |
| [44] | Face mask detection using deep learning: An approach to reduce risk of Coronavirus spread | Sethi, S. | Original Research |
| [45] | Visual analytics of COVID-19 dissemination in Sao Paulo state, Brazil | Marcilio-Jr, W. E. | Original Research |
| [46] | COnVIDa: COVID-19 multidisciplinary data collection and dashboard | Martinez Beltran, E. T. | Special Communication |
| [47] | Factors influencing mHealth adoption and its impact on mental well-being during COVID-19 pandemic: A SEM-ANN approach | Alam, M. M. D. | Special Communication |