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4. Joint approaches for learning word representations from text corpora and knowledge bases

Author

Alsuhaibani, Mohammed

Subjects
006.3
Abstract

The work presented in this thesis is directed at investigating the possibility of combining text corpora and Knowledge Bases (KBs) for learning word representations. More specifically, the aim was to propose joint approaches that leverage the two types of resources for the purpose of enhancing the word meaning representations. The main research question to be answered was “Is it possible to enhance the word representations by jointly incorporating text corpora and KBs into the word representations learning process? If so, what are the aspects of word meaning that can be enhanced by combining those two types of resources? ”. The primary contribution of the thesis is three main joint approaches for learning word representations: (i) Joint Representation Learning for Additional Evidence (JointReps), (ii) Joint Hierarchical Word Representation (HWR) and (iii) Sense-Aware Word Representations (SAWR). The JointReps was founded to improve the overall semantic representation of words. To this end, it sought additional evidence from a KB to the co-occurrence statistics in the corpus. In particular, JointReps enforced two words that are in a particular semantic relationship in the KB to have similar word representations. The HWR approach was then proposed to learn word representations in a specific order to encode the hierarchical information in a KB in the learnt representations. The HWR considered not only the hypernym relations that exist between words in a KB, but also contextual information in a text corpus. Specifically, given a training corpus and a KB, HWR learnt word representations that simultaneously encoded the hierarchical structure in the KB as well as the co-occurrence statistics between pairs of words in the corpus. A particularly novel aspect of the HWR approach was that it exploits the full hierarchical path of words existing in the KB. The SAWR approach was then introduced to consider not only word representations but also the different senses (different meanings) associated with each word. The SAWR required the learnt representations to predict the word and the senses accurately. It learnt the sense-aware word representations jointly using both unlabelled and sense-labelled text corpora. The approaches were comprehensively analysed and evaluated in various standard and newly-proposed tasks using a wide range of benchmark datasets. The evaluation was conducted to compare the quality of the learnt word representations by the proposed approaches with word representations learnt by sole-resource baselines and previously proposed joint approaches in the literature. All the proposed joint approaches have proven to be effective for enhancing the learnt word representations. More specifically, the proposed joint approaches were found to report significant improvements over the approaches that use only one type of resources and the previously proposed joint approaches.

Published
2020
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5. Epidemiology, clinical profiles, and antimicrobial susceptibility of Elizabethkingia meningoseptica infections: Insights from a tertiary care hospital in Saudi Arabia.

Author

Alhuthil, Raghad T., Hijazi, Raghad M., Alyabes, Ohoud A., Alsuhaibani, Mohammed A., Gashgarey, Deema A., Binsalamah, Ibrahim M., Aldahmash, Mohammed A., Alghamdi, Salem M., Albanyan, Esam A., Aljumaah, Suliman A., and Al-Hajjar, Sami H.

Subjects
TERTIARY care, HOSPITAL mortality, AGE groups, EPIDEMIOLOGY, DEATH rate, ENTEROCOCCAL infections, CARDIOVASCULAR diseases
Abstract

Copyright of Saudi Medical Journal is the property of Saudi Medical Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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13. Assessing the Precision of Surgery Duration Estimation: A Retrospective Study

Author

Aljaffary,Afnan, AlAnsari,Fatimah, Alatassi,Abdulaleem, AlSuhaibani,Mohammed, and Alomran,Ammar

Subjects
Journal of Multidisciplinary Healthcare
Abstract

Afnan Aljaffary,1 Fatimah AlAnsari,1 Abdulaleem Alatassi,2 Mohammed AlSuhaibani,3 Ammar Alomran4 1Health Information Management and Technology Department, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia; 2Preoperative Quality and Patient Safety Department, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia; 3Operating Room Services Department, King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia; 4Department of Orthopedic, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi ArabiaCorrespondence: Afnan Aljaffary, Tel +9661333, Email aaljaffari@iau.edu.saBackground and Objectives: The operating room (OR) is considered the highest source of cost and earnings. Therefore, measuring OR efficiency, which means how time and resources are allocated precisely for their intended purposes in the operating room is crucial. Both overestimation and underestimation negatively impact OR efficiency Therefore, hospitals defined metrics to Measuring OR Effeciency. Many studies have discussed OR efficiency and how surgery scheduling accuracy plays a vital role in increasing OR efficiency. This study aims to evaluate OR efficiency using surgery duration accuracy.Methods: This retrospective, quantitative study was conducted at King Abdulaziz Medical City. We extracted data on 97,397 surgeries from 2017 to 2021 from the OR database. The accuracy of surgery duration was identified by calculating the duration of each surgery in minutes by subtracting the time of leaving the OR from the time of entering the OR. Based on the scheduled duration, the calculated durations were categorized as either underestimation or overestimation. Descriptive and bivariate analyses (Chi-square test) were performed using the Statistical Package for the Social Sciences (SPSS) software.Results: Sixty percent out of the 97,397 surgeries performed were overestimated compared to the time scheduled by the surgeons. Patient characteristics, surgical division, and anesthesia type showed statistically significant differences (p < 0.05) in their OR estimation.Conclusion: Significant proportion of procedures have overestimated. This finding provides insight into the need for improvement.Recommendations: It is recommended to enhance the surgical scheduling method using machine learning (ML) models to include patient characteristics, department, anesthesia type, and even the performing surgeon increases the accuracy of duration estimation. Then, evaluate the performance of an ML model in future studies.Keywords: efficiency, operating room, overestimation, underestimation, Saudi Arabia

Published
2023

17. The effectiveness of COVID-19 vaccine in the prevention of post-COVID conditions: a systematic literature review and meta-analysis of the latest research

Author

Marra, Alexandre R., primary, Kobayashi, Takaaki, additional, Callado, Gustavo Yano, additional, Pardo, Isabele, additional, Gutfreund, Maria Celidonio, additional, Hsieh, Mariana Kim, additional, Lin, Vivian, additional, Alsuhaibani, Mohammed, additional, Hasegawa, Shinya, additional, Tholany, Joseph, additional, Perencevich, Eli N., additional, Salinas, Jorge L., additional, Edmond, Michael B., additional, and Rizzo, Luiz Vicente, additional

Published
2023
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22. Content-Based Approach for Improving Bloom Filter Efficiency.

Author

Alsuhaibani, Mohammed, Khan, Rehan Ullah, Qamar, Ali Mustafa, and Alsuhibany, Suliman A.

Subjects
NETWORK routers, DATABASES
Abstract

Bloom filters are a type of data structure that is used to test whether or not an element is a member of a set. They are known for being space-efficient and are commonly employed in various applications, such as network routers, web browsers, and databases. These filters work by allowing a fixed probability of incorrectly identifying an element as being a member of the set, known as the false positive rate (FPR). However, traditional bloom filters suffer from a high FPR and extensive memory usage, which can lead to incorrect query results and a slow performance. Thus, this study indicates that a content-based strategy could be a practical solution for these challenges. Specifically, our approach requires less bloom filter storage, consequently decreasing the probability of false positives. The effectiveness of several hash functions on our strategy's performance was also evaluated. Experimental evaluations demonstrated that the proposed strategy could potentially decrease false positives by a substantial margin of up to 79.83%. The use of size-based content bits significantly contributes to the decrease in the number of false positives as well. However, as the volume of content bits rises, the impact on time is not considerably noticeable. Moreover, the evidence suggests that the application of a singular approach leads to a more than 50% decrease in false positives. [ABSTRACT FROM AUTHOR]

Published
2023
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23. Leveraging Graph-Based Representations to Enhance Machine Learning Performance in IIoT Network Security and Attack Detection.

Author

Alwasel, Bader, Aldribi, Abdulaziz, Alreshoodi, Mohammed, Alsukayti, Ibrahim S., and Alsuhaibani, Mohammed

Subjects
MACHINE learning, INTRUSION detection systems (Computer security), MACHINE performance, NETWORK performance, GRAPH theory, REPRESENTATIONS of graphs, COMPUTER network security
Abstract

In the dynamic and ever-evolving realm of network security, the ability to accurately identify and classify portscan attacks both inside and outside networks is of paramount importance. This study delves into the underexplored potential of fusing graph theory with machine learning models to elevate their anomaly detection capabilities in the context of industrial Internet of things (IIoT) network data analysis. We employed a comprehensive experimental approach, encompassing data preprocessing, visualization, feature analysis, and machine learning model comparison, to assess the efficacy of graph theory representation in improving classification accuracy. More specifically, we converted network traffic data into a graph-based representation, where nodes represent devices and edges represent communication instances. We then incorporated these graph features into our machine learning models. Our findings reveal that incorporating graph theory into the analysis of network data results in a modest-yet-meaningful improvement in the performance of the tested machine learning models, including logistic regression, support vector machines, and K-means clustering. These results underscore the significance of graph theory representation in bolstering the discriminative capabilities of machine learning algorithms when applied to network data. [ABSTRACT FROM AUTHOR]

Published
2023
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24. Coronavirus disease 2019 (COVID-19) among nonphysician healthcare personnel by work location at a tertiary-care center, Iowa, 2020–2021

Author

Kobayashi, Takaaki, primary, Heinemann, John, additional, Trannel, Alexandra, additional, Marra, Alexandre R., additional, Alsuhaibani, Mohammed, additional, Etienne, William, additional, Sheeler, Lorinda L., additional, Abosi, Oluchi, additional, Holley, Stephanie, additional, Kukla, Mary Beth, additional, Dains, Angelique, additional, Jenn, Kyle E., additional, Meacham, Holly, additional, Hanna, Beth, additional, Ford, Bradley, additional, Brust, Karen, additional, Wellington, Melanie, additional, Hartley, Patrick G., additional, Diekema, Daniel J., additional, and Salinas, Jorge L., additional

Published
2022
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25. Impact of COVID-19 on an infection prevention and control program, Iowa 2020-2021

Author

Alsuhaibani, Mohammed, primary, Kobayashi, Takaaki, additional, McPherson, Chad, additional, Holley, Stephanie, additional, Marra, Alexandre R., additional, Trannel, Alexandra, additional, Dains, Angelique, additional, Abosi, Oluchi J., additional, Jenn, Kyle E., additional, Meacham, Holly, additional, Sheeler, Lorinda, additional, Etienne, William, additional, Kukla, Mary E., additional, Wellington, Melanie, additional, Edmond, Michael B., additional, Diekema, Daniel J., additional, and Salinas, Jorge L., additional

Published
2022
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26. Short-term effectiveness of COVID-19 vaccines in immunocompromised patients: A systematic literature review and meta-analysis

Author

Marra, Alexandre R., primary, Kobayashi, Takaaki, additional, Suzuki, Hiroyuki, additional, Alsuhaibani, Mohammed, additional, Tofaneto, Bruna Marques, additional, Bariani, Luigi Makowski, additional, Auler, Mariana de Amorim, additional, Salinas, Jorge L., additional, Edmond, Michael B., additional, Doll, Michelle, additional, Kutner, José Mauro, additional, Pinho, João Renato Rebello, additional, Rizzo, Luiz Vicente, additional, Miraglia, João Luiz, additional, and Schweizer, Marin L., additional

Published
2022
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27. Attitudes Towards Complementary and Alternative Medicine Among Pediatricians in Saudi Arabia

Author

Alnafia, Alwaleed, Binyousef, Faris H, Algwaiz, Abdulrahman, Almazyed, Anas, Alduaylij, Tariq, Alolaiwi, Osama, Alajlan, Abdullah, Alsuhaibani, Mohammed, and Alenazi, Kamel A

Subjects
children, Integrative/Complementary Medicine, attitude, saudi arabia, General Engineering, pediatricians, Pediatrics, complementary and alternative medicine
Abstract

Background Complementary and Alternative Medicine (CAM) refers to a variety of healthcare practices outside the domain of conventional medicine, which may be integrated with conventional medicine by many physicians. Objectives This study aims to assess the attitudes and beliefs of pediatricians toward the use of CAM on children and to evaluate their knowledge and experience regarding CAM therapies and their desire for additional CAM training courses. Methods This is a cross-sectional study that was conducted in Saudi Arabia. A self-administered electronic questionnaire consisting of 27 questions was distributed among pediatricians to assess the demographics, beliefs, experiences, and attitudes of pediatricians related to the use of CAM for children. Non-probability convenience sampling was used in selecting the sample of pediatricians. Data analysis was performed using SPSS version 21 (IBM Corp., Armonk, NY). Results In this study, 140 participants completed the questionnaires. Most of the participants were of the male gender (83, 59.3%) and Saudi nationals (127, 90.7%). With regards to questions related to the experiences and opinions of participants regarding the use of CAM, 101 (72.1%) subjects reported the use of CAM among family members. Pediatricians cited affirmative encounters of use of CAM in 94 (67.1%) by parents. Pediatricians were not in favor of the use of CAM for end-stage (114, 81.4%) and chronic disease (108, 77.1%). The overall median self-reported CAM knowledge score was statistically higher for males in comparison with females [3 (IQR 1-5)] versus 2 (IQR 2-4), P = 0.030]. Also for nationality, median scores were significantly greater for the Riyadh region in contrast to other regions [[3 (IQR 2-5)] versus 2 (IQR 1-4), P = 0.041]. There was a significant difference in median scores for qualification of participants (P = 0.002). A multiple pairwise comparison revealed a statistically significant (P = 0.012) difference between participants with the qualification of residents and specialization. No differences in median CAM scores were found for responses related to the experiences, opinions, and attitudes of pediatricians towards the use of CAM therapies. Conclusion Most of the pediatricians in Saudi Arabia don’t recommend the use of CAM treatment in their practice, but they acknowledge that learning more about CAM and imparting appropriate knowledge regarding it may incorporate its use in their routine clinical practices in a safe way.

Published
2021

28. Coronavirus disease 2019 (COVID-19) among nonphysician healthcare personnel by work location at a tertiary-care center, Iowa, 2020–2021

Author

Kobayashi, Takaaki, Heinemann, John, Trannel, Alexandra, Marra, Alexandre R., Alsuhaibani, Mohammed, Etienne, William, Sheeler, Lorinda L., Abosi, Oluchi, Holley, Stephanie, Kukla, Mary Beth, Dains, Angelique, Jenn, Kyle E., Meacham, Holly, Hanna, Beth, Ford, Bradley, Brust, Karen, Wellington, Melanie, Hartley, Patrick G., Diekema, Daniel J., and Salinas, Jorge L.

Abstract

AbstractWe describe COVID-19 cases among nonphysician healthcare personnel (HCP) by work location. The proportion of HCP with coronavirus disease 2019 (COVID-19) was highest in the emergency department and lowest among those working remotely. COVID-19 and non–COVID-19 units had similar proportions of HCP with COVID-19 (13%). Cases decreased across all work locations following COVID-19 vaccination.

Published
2023
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31. The long-term effectiveness of coronavirus disease 2019 (COVID-19) vaccines: A systematic literature review and meta-analysis

Author

Marra, Alexandre R., primary, Kobayashi, Takaaki, additional, Suzuki, Hiroyuki, additional, Alsuhaibani, Mohammed, additional, Schweizer, Marin L., additional, Diekema, Daniel J., additional, Tofaneto, Bruna Marques, additional, Bariani, Luigi Makowski, additional, Auler, Mariana de Amorim, additional, Salinas, Jorge L., additional, Edmond, Michael B., additional, Pinho, João Renato Rebello, additional, and Rizzo, Luiz Vicente, additional

Published
2022
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33. The effectiveness of coronavirus disease 2019 (COVID-19) vaccine in the prevention of post–COVID-19 conditions: A systematic literature review and meta-analysis

Author

Marra, Alexandre R., primary, Kobayashi, Takaaki, additional, Suzuki, Hiroyuki, additional, Alsuhaibani, Mohammed, additional, Hasegawa, Shinya, additional, Tholany, Joseph, additional, Perencevich, Eli, additional, Maezato, Aline Miho, additional, Ricardo, Victoria Catharina Volpe, additional, Salinas, Jorge L., additional, Edmond, Michael B., additional, and Rizzo, Luiz Vicente, additional

Published
2022
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35. Stable Clostridioides difficile infection rates after the discontinuation of ultraviolet light for terminal disinfection at a tertiary care center, Iowa 2019-2020

Author

Abosi, Oluchi J., primary, Kobayashi, Takaaki, additional, Holley, Stephanie, additional, Kukla, Mary Elizabeth, additional, Dains, Angelique, additional, Alsuhaibani, Mohammed, additional, Marra, Alexandre R., additional, Jenn, Kyle E., additional, Meacham, Holly, additional, Sheeler, Lorinda L., additional, Etienne, William, additional, Trannel, Alexandra, additional, Garringer, Jon, additional, Millard, William, additional, Diekema, Daniel J., additional, Edmond, Michael B., additional, Wellington, Melanie, additional, and Salinas, Jorge L., additional

Published
2021
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36. The Impact of Check Bits on the Performance of Bloom Filter.

Author

Khan, Rehan Ullah, Qamar, Ali Mustafa, Alsuhibany, Suliman A., and Alsuhaibani, Mohammed

Subjects
FALSE positive error, INFORMATION retrieval
Abstract

Bloom filter (BF) is a space-and-time efficient probabilistic technique that helps answermembership queries. However, BF faces several issues. The problems with traditional BF are generally two. Firstly, a large number of false positives can return wrong content when the data is queried. Secondly, the large size of BF is a bottleneck in the speed of querying and thus uses large memory. In order to solve the above two issues, in this article, we propose the check bits concept. From the implementation perspective, in the check bits approach, before saving the content value in the BF, we obtain the binary representation of the content value. Then, we take some bits of the content value, we call these the check bits. These bits are stored in a separate array such that they point to the same location as the BF. Finally, the content value (data) is stored in the BF based on the hash function values. Before retrieval of data from BF, the reverse process of the steps ensures that even if the same hash functions output has been generated for the content, the check bits make sure that the retrieval does not depend on the hash output alone. This thus helps in the reduction of false positives. In the experimental evaluation, we are able to reduce more than 50% of false positives. In our proposed approach, the false positives can still occur, however, false positives can only occur if the hash functions and check bits generate the same value for a particular content. The chances of such scenarios are less, therefore, we get a reduction of approximately more than 50% false positives in all cases. We believe that the proposed approach adds to the state of the art and opens new directions as such. [ABSTRACT FROM AUTHOR]

Published
2022
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38. Bat intrusions at a tertiary care center in Iowa, 2018–2020

Author

Alsuhaibani, Mohammed A., primary, Dains, Angelique, additional, Kobayashi, Takaaki, additional, Sheeler, Lorinda L., additional, Trannel, Alexandra, additional, Holley, Stephanie, additional, Marra, Alexandre R., additional, Abosi, Oluchi J., additional, Jenn, Kyle E., additional, Meacham, Holly, additional, Etienne, William, additional, Kukla, Mary E., additional, Millard, Bill, additional, Wellington, Melanie, additional, Diekema, Daniel J., additional, and Salinas, Jorge L., additional

Published
2021
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39. Coronavirus disease 2019 (COVID-19) incidence after exposures in shared patient rooms in a tertiary-care center in Iowa, July 2020–May 2021

Author

Trannel, Alexandra M., primary, Kobayashi, Takaaki, additional, Dains, Angelique, additional, Abosi, Oluchi J., additional, Jenn, Kyle E., additional, Meacham, Holly, additional, Sheeler, Lorinda L., additional, Etienne, William, additional, Kukla, Mary E., additional, Alsuhaibani, Mohammed, additional, Holley, Stephanie, additional, Strandberg, Kelsey, additional, Marra, Alexandre R., additional, Kritzman, Jeffrey, additional, Ford, Bradley, additional, Wellington, Melanie, additional, Diekema, Daniel J., additional, and Salinas, Jorge L., additional

Published
2021
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40. Bat Intrusions at a Tertiary Care Center, Iowa 2018–2020

Author

Alsuhaibani, Mohammed, primary, Kobayashi, Takaaki, additional, Sheeler, Lorinda, additional, Trannel, Alexandra, additional, Holley, Stephanie, additional, Abosi, Oluchi, additional, Jenn, Kyle, additional, Meacham, Holly, additional, Etienne, William, additional, Dains, Angie, additional, Kukla, Mary, additional, Millard, Bill, additional, Marra, Alexandre, additional, Wellington, Melanie, additional, Diekema, Daniel, additional, and Salinas, Jorge, additional

Published
2021
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41. Suspected COVID-19 Reinfections at a Tertiary Care Center, Iowa 2020

Author

Kobayashi, Takaaki, primary, Alsuhaibani, Mohammed, additional, Ortiz, Miguel, additional, Imborek, Katherine, additional, Holley, Stephanie, additional, Trannel, Alexandra, additional, Marra, Alexandre, additional, Etienne, William, additional, Jenn, Kyle, additional, Abosi, Oluchi, additional, Meacham, Holly, additional, Sheeler, Lorinda, additional, Dains, Angie, additional, Kukla, Mary, additional, McCray, Paul, additional, Perlman, Stanley, additional, Ford, Bradley, additional, Diekema, Daniel, additional, Wellington, Melanie, additional, Pezzulo, Alejandro, additional, and Salinas, Jorge, additional

Published
2021
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42. COVID-19 Conversion after Exposure in a Semiprivate Room at a Tertiary Care Center in Iowa, July–December 2020

Author

Trannel, Alexandra, primary, Kobayashi, Takaaki, additional, Abosi, Oluchi, additional, Jenn, Kyle, additional, Meacham, Holly, additional, Sheeler, Lorinda, additional, Etienne, William, additional, Dains, Angie, additional, Kukla, Mary, additional, Alsuhaibani, Mohammed, additional, Holley, Stephanie, additional, Marra, Alexandre, additional, Ford, Bradley, additional, Wellington, Melanie, additional, Diekema, Daniel, additional, and Salinas, Jorge, additional

Published
2021
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43. Coronavirus Disease 2019 (COVID-19) Admission Screening at a Tertiary-Care Center, Iowa 2020

Author

Alsuhaibani, Mohammed, primary, Kobayashi, Takaaki, additional, Trannel, Alexandra, additional, Holley, Stephanie, additional, Abosi, Oluchi, additional, Jenn, Kyle, additional, Meacham, Holly, additional, Sheeler, Lorinda, additional, Etienne, William, additional, Dains, Angie, additional, Kukla, Mary, additional, Ward, Emily, additional, Ford, Bradley, additional, Edmond, Michael, additional, Wellington, Melanie, additional, Diekema, Daniel, additional, and Salinas, Jorge, additional

Published
2021
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44. Impact of COVID-19 on Volume of Infection Prevention and Control Calls at a Tertiary-Care Center in Iowa, 2018–2020

Author

Alsuhaibani, Mohammed, primary, Kobayashi, Takaaki, additional, Holley, Stephanie, additional, Dains, Angie, additional, Abosi, Oluchi, additional, Jenn, Kyle, additional, Meacham, Holly, additional, Sheeler, Lorinda, additional, Etienne, William, additional, Trannel, Alexandra, additional, Kukla, Mary, additional, Marra, Alexandre, additional, Wellington, Melanie, additional, Diekema, Daniel, additional, and Salinas, Jorge, additional

Published
2021
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45. Molecular Epidemiology of Large COVID-19 Clusters at an Academic Medical Center, March–October 2020

Author

Kobayashi, Takaaki, primary, Ortiz, Miguel, additional, Holley, Stephanie, additional, Etienne, William, additional, Jenn, Kyle, additional, Abosi, Oluchi, additional, Meacham, Holly, additional, Sheeler, Lorinda, additional, Dains, Angie, additional, Kukla, Mary, additional, Trannel, Alexandra, additional, Marra, Alexandre, additional, Alsuhaibani, Mohammed, additional, McCray, Paul, additional, Perlman, Stanley, additional, Ford, Bradley, additional, Diekema, Daniel, additional, Wellington, Melanie, additional, Pezzulo, Alejandro, additional, and Salinas, Jorge, additional

Published
2021
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46. Coronavirus disease 2019 (COVID-19) admission screening and assessment of infectiousness at an academic medical center in Iowa, 2020

Author

Alsuhaibani, Mohammed A., primary, Kobayashi, Takaaki, additional, Trannel, Alexandra, additional, Holley, Stephanie, additional, Abosi, Oluchi J., additional, Jenn, Kyle E., additional, Meacham, Holly, additional, Sheeler, Lorinda, additional, Etienne, William, additional, Dains, Angelique, additional, Kukla, Mary E., additional, Ward, Emily, additional, Ford, Bradley, additional, Edmond, Michael B., additional, Wellington, Melanie, additional, Diekema, Daniel J., additional, and Salinas, Jorge L., additional

Published
2021
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47. Molecular epidemiology of large coronavirus disease 2019 (COVID-19) clusters before and after the implementation of routine serial testing at an academic medical center in Iowa, 2020

Author

Ortiz, Miguel E., primary, Kobayashi, Takaaki, additional, Imborek, Katherine, additional, Alsuhaibani, Mohammed, additional, Holley, Stephanie, additional, Trannel, Alexandra, additional, Marra, Alexandre R., additional, Etienne, William, additional, Jenn, Kyle E., additional, Abosi, Oluchi J., additional, Meacham, Holly, additional, Sheeler, Lorinda, additional, Dains, Angelique, additional, Kukla, Mary E., additional, McCray, Paul B., additional, Perlman, Stanley, additional, Ford, Bradley, additional, Diekema, Daniel J., additional, Wellington, Melanie, additional, Pezzulo, Alejandro A., additional, and Salinas, Jorge L., additional

Published
2021
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48. Coronavirus disease 2019 (COVID-19) incidence after exposures in shared patient rooms in a tertiary-care center in Iowa, July 2020–May 2021

Author

Trannel, Alexandra M., Kobayashi, Takaaki, Dains, Angelique, Abosi, Oluchi J., Jenn, Kyle E., Meacham, Holly, Sheeler, Lorinda L., Etienne, William, Kukla, Mary E., Alsuhaibani, Mohammed, Holley, Stephanie, Strandberg, Kelsey, Marra, Alexandre R., Kritzman, Jeffrey, Ford, Bradley, Wellington, Melanie, Diekema, Daniel J., and Salinas, Jorge L.

Abstract

AbstractThe incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure in shared patient rooms was low at our institution: 1.8 per 1,000 shared-room patient days. However, the secondary attack rate (21.6%) was comparable to that reported in household exposures. Lengthier exposures were associated with SARS-CoV-2 conversion. Hospitals should implement measures to decrease shared-room exposures.

Published
2022
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49. The Impact of COVID-19 Pandemic Lockdown on the Incidence of New-Onset Type 1 Diabetes and Ketoacidosis Among Saudi Children

Author

Alaqeel, Aqeel, primary, Aljuraibah, Fahad, additional, Alsuhaibani, Mohammed, additional, Huneif, Mohammed, additional, Alsaheel, Abdulhameed, additional, Dubayee, Mohammad Al, additional, Alsaedi, Abdulaziz, additional, Bakkar, Ayman, additional, Alnahari, Ahmed, additional, Taha, Areej, additional, Alharbi, Khulood, additional, Alanazi, Yousef, additional, Almadhi, Samia, additional, and Khalifah, Reem Al, additional

Published
2021
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