Full Text Journal Articles by
Author Aaron J Masino

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Multinational characterization of neurological phenotypes in patients hospitalized with COVID-19.

Trang T Le, Alba Gutiérrez-Sacristán, Jiyeon Son, Chuan Hong, Andrew M South, Brett K Beaulieu-Jones, Ne Hooi Will Loh, Yuan Luo, Michele Morris, Kee Yuan Ngiam, Lav P Patel, Malarkodi J Samayamuthu, Emily Schriver, Amelia L M Tan, Jason Moore, Tianxi Cai, Gilbert S Omenn, Paul Avillach, Isaac S Kohane, , Shyam Visweswaran, Danielle L Mowery, Zongqi Xia,

Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents ... Read more >>

Sci Rep (Scientific reports)
[2021, 11(1):20238]

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International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study.

Griffin M Weber, Harrison G Zhang, Sehi L'Yi, Clara-Lea Bonzel, Chuan Hong, Paul Avillach, Alba Gutiérrez-Sacristán, Nathan P Palmer, Amelia Li Min Tan, Xuan Wang, William Yuan, Nils Gehlenborg, Anna Alloni, Danilo F Amendola, Antonio Bellasi, Riccardo Bellazzi, Michele Beraghi, Mauro Bucalo, Luca Chiovato, Kelly Cho, Arianna Dagliati, Hossein Estiri, Robert W Follett, Noelia García Barrio, David A Hanauer, Darren W Henderson, Yuk-Lam Ho, John H Holmes, Meghan R Hutch, Ramakanth Kavuluru, Katie Kirchoff, Jeffrey G Klann, Ashok K Krishnamurthy, Trang T Le, Molei Liu, Ne Hooi Will Loh, Sara Lozano-Zahonero, Yuan Luo, Sarah Maidlow, Adeline Makoudjou, Alberto Malovini, Marcelo Roberto Martins, Bertrand Moal, Michele Morris, Danielle L Mowery, Shawn N Murphy, Antoine Neuraz, Kee Yuan Ngiam, Marina P Okoshi, Gilbert S Omenn, Lav P Patel, Miguel Pedrera Jiménez, Robson A Prudente, Malarkodi Jebathilagam Samayamuthu, Fernando J Sanz Vidorreta, Emily R Schriver, Petra Schubert, Pablo Serrano Balazote, Byorn Wl Tan, Suzana E Tanni, Valentina Tibollo, Shyam Visweswaran, Kavishwar B Wagholikar, Zongqi Xia, Daniela Zöller, , Isaac S Kohane, Tianxi Cai, Andrew M South, Gabriel A Brat,

<h4>Background</h4>Many countries have experienced 2 predominant waves of COVID-19-related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic.<h4>Objective</h4>In this retrospective cohort study, we analyzed electronic health record (EHR) data ... Read more >>

J Med Internet Res (Journal of medical Internet research)
[2021, 23(10):e31400]

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Evolving phenotypes of non-hospitalized patients that indicate long COVID.

Hossein Estiri, Zachary H Strasser, Gabriel A Brat, Yevgeniy R Semenov, , Chirag J Patel, Shawn N Murphy,

<h4>Background</h4>For some SARS-CoV-2 survivors, recovery from the acute phase of the infection has been grueling with lingering effects. Many of the symptoms characterized as the post-acute sequelae of COVID-19 (PASC) could have multiple causes or are similarly seen in non-COVID patients. Accurate identification of PASC phenotypes will be important to guide ... Read more >>

BMC Med (BMC medicine)
[2021, 19(1):249]

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International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries.

Florence T Bourgeois, Alba Gutiérrez-Sacristán, Mark S Keller, Molei Liu, Chuan Hong, Clara-Lea Bonzel, Amelia L M Tan, Bruce J Aronow, Martin Boeker, John Booth, Jaime Cruz Rojo, Batsal Devkota, Noelia García Barrio, Nils Gehlenborg, Alon Geva, David A Hanauer, Meghan R Hutch, Richard W Issitt, Jeffrey G Klann, Yuan Luo, Kenneth D Mandl, Chengsheng Mao, Bertrand Moal, Karyn L Moshal, Shawn N Murphy, Antoine Neuraz, Kee Yuan Ngiam, Gilbert S Omenn, Lav P Patel, Miguel Pedrera Jiménez, Neil J Sebire, Pablo Serrano Balazote, Arnaud Serret-Larmande, Andrew M South, Anastasia Spiridou, Deanne M Taylor, Patric Tippmann, Shyam Visweswaran, Griffin M Weber, Isaac S Kohane, Tianxi Cai, Paul Avillach, ,

<h4>Importance</h4>Additional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients.<h4>Objective</h4>To describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19.<h4>Design, setting, and participants</h4>This retrospective cohort study ... Read more >>

JAMA Netw Open (JAMA network open)
[2021, 4(6):e2112596]

Cited: 1 time

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Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

Brian Huang, Robin Wang, Aaron J Masino, Amrom E Obstfeld,

<h4>Introduction</h4>Early diagnosis and antibiotic administration are essential for reducing sepsis morbidity and mortality; however, diagnosis remains difficult due to complex pathogenesis and presentation. We created a machine learning model for bacterial sepsis identification in the neonatal intensive care unit (NICU) using hematological analyzer data.<h4>Methods</h4>Hematological analyzer data were gathered from NICU ... Read more >>

Int J Lab Hematol (International journal of laboratory hematology)
[2021, :]

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Fasting Duration and Blood Pressure in Children: Reply.

Allan F Simpao, Lezhou Wu, Olivia Nelson, Jorge A Gálvez, Jonathan M Tan, Jack O Wasey, Wallis T Muhly, Fu-Chiang Tsui, Aaron J Masino, Paul A Stricker,

Anesthesiology (Anesthesiology)
[2021, 134(4):668-669]

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Prediction of early childhood obesity with machine learning and electronic health record data.

Xueqin Pang, Christopher B Forrest, Félice Lê-Scherban, Aaron J Masino,

<h4>Objective</h4>This study compares seven machine learning models developed to predict childhood obesity from age > 2 to ≤ 7 years using Electronic Healthcare Record (EHR) data up to age 2 years.<h4>Materials and methods</h4>EHR data from of 860,510 patients with 11,194,579 healthcare encounters were obtained from the Children's Hospital of Philadelphia. ... Read more >>

Int J Med Inform (International journal of medical informatics)
[2021, 150:104454]

Cited: 1 time

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Personalized prediction of early childhood asthma persistence: A machine learning approach.

Saurav Bose, Chén C Kenyon, Aaron J Masino,

Early childhood asthma diagnosis is common; however, many children diagnosed before age 5 experience symptom resolution and it remains difficult to identify individuals whose symptoms will persist. Our objective was to develop machine learning models to identify which individuals diagnosed with asthma before age 5 continue to experience asthma-related visits. ... Read more >>

PLoS One (PloS one)
[2021, 16(3):e0247784]

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Supervised Machine Learning Applied to Automate Flash and Prolonged Capillary Refill Detection by Pulse Oximetry.

Ryan Brandon Hunter, Shen Jiang, Akira Nishisaki, Amanda J Nickel, Natalie Napolitano, Koichiro Shinozaki, Timmy Li, Kota Saeki, Lance B Becker, Vinay M Nadkarni, Aaron J Masino,

<h4>Objective</h4>Develop an automated approach to detect flash (<1.0 s) or prolonged (>2.0 s) capillary refill time (CRT) that correlates with clinician judgment by applying several supervised machine learning (ML) techniques to pulse oximeter plethysmography data.<h4>Materials and methods</h4>Data was collected in the Pediatric Intensive Care Unit (ICU), Cardiac ICU, Progressive Care ... Read more >>

Front Physiol (Frontiers in physiology)
[2020, 11:564589]

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Preoperative Fluid Fasting Times and Postinduction Low Blood Pressure in Children: A Retrospective Analysis.

Allan F Simpao, Lezhou Wu, Olivia Nelson, Jorge A Gálvez, Jonathan M Tan, Jack O Wasey, Wallis T Muhly, Fu-Chiang Tsui, Aaron J Masino, Paul A Stricker,

<h4>Background</h4>Children are required to fast before elective general anesthesia. This study hypothesized that prolonged fasting causes volume depletion that manifests as low blood pressure. This study aimed to assess the association between fluid fasting duration and postinduction low blood pressure.<h4>Methods</h4>A retrospective cohort study was performed of 15,543 anesthetized children without ... Read more >>

Anesthesiology (Anesthesiology)
[2020, 133(3):523-533]

Cited: 1 time

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Identification of temporal condition patterns associated with pediatric obesity incidence using sequence mining and big data.

Elizabeth A Campbell, Ting Qian, Jeffrey M Miller, Ellen J Bass, Aaron J Masino,

<h4>Background</h4>Electronic health records (EHRs) are potentially important components in addressing pediatric obesity in clinical settings and at the population level. This work aims to identify temporal condition patterns surrounding obesity incidence in a large pediatric population that may inform clinical care and childhood obesity policy and prevention efforts.<h4>Methods</h4>EHR data from ... Read more >>

Int J Obes (Lond) (International journal of obesity (2005))
[2020, 44(8):1753-1765]

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Perspective on the Development of a Large-Scale Clinical Data Repository for Pediatric Hearing Research.

Jeffrey W Pennington, Byron Ruth, Jeffrey M Miller, Joy Peterson, Baichen Xu, Aaron J Masino, Ian Krantz, Juliana Manganella, Tamar Gomes, Derek Stiles, Margaret Kenna, Linda J Hood, John Germiller, E Bryan Crenshaw,

The use of "big data" for pediatric hearing research requires new approaches to both data collection and research methods. The widespread deployment of electronic health record systems creates new opportunities and corresponding challenges in the secondary use of large volumes of audiological and medical data. Opportunities include cost-effective hypothesis generation, ... Read more >>

Ear Hear (Ear and hearing)
[2020, 41(2):231-238]

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Temporal condition pattern mining in large, sparse electronic health record data: A case study in characterizing pediatric asthma.

Elizabeth A Campbell, Ellen J Bass, Aaron J Masino,

<h4>Objective</h4>This study introduces a temporal condition pattern mining methodology to address the sparse nature of coded condition concept utilization in electronic health record data. As a validation study, we applied this method to reveal condition patterns surrounding an initial diagnosis of pediatric asthma.<h4>Materials and methods</h4>The SPADE (Sequential PAttern Discovery using ... Read more >>

J Am Med Inform Assoc (Journal of the American Medical Informatics Association : JAMIA)
[2020, 27(4):558-566]

Cited: 1 time

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Unsupervised Machine Learning Reveals Novel Traumatic Brain Injury Patient Phenotypes with Distinct Acute Injury Profiles and Long-Term Outcomes.

Kaitlin A Folweiler, Danielle K Sandsmark, Ramon Diaz-Arrastia, Akiva S Cohen, Aaron J Masino,

The heterogeneity of traumatic brain injury (TBI) remains a core challenge for the success of interventional clinical trials. Data-driven approaches for patient stratification may help to identify TBI patient phenotypes during the acute injury period as well as facilitate targeted trial patient enrollment and analysis of treatment efficacy. In this ... Read more >>

J Neurotrauma (Journal of neurotrauma)
[2020, 37(12):1431-1444]

Cited: 3 times

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Neonatal sepsis registry: Time to antibiotic dataset.

Svetlana Ostapenko, Melissa Schmatz, Lakshmi Srinivasan, Okan U Elci, Scott L Weiss, Aaron J Masino, Marissa Tremoglie, Mary Catherine Harris, Robert W Grundmeier,

This article describes the process of extracting electronic health record (EHR) data into a format that supports analyses related to the timeliness of antibiotic administration. The de-identified data that accompanies this article were collected from a cohort of infants who were evaluated for possible sepsis in the Neonatal Intensive Care ... Read more >>

Data Brief (Data in brief)
[2019, 27:104788]

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Surviving Sepsis in a Referral Neonatal Intensive Care Unit: Association between Time to Antibiotic Administration and In-Hospital Outcomes.

Melissa Schmatz, Lakshmi Srinivasan, Robert W Grundmeier, Okan U Elci, Scott L Weiss, Aaron J Masino, Marissa Tremoglie, Svetlana Ostapenko, Mary Catherine Harris,

<h4>Objective</h4>To determine if time to antibiotic administration is associated with mortality and in-hospital outcomes in a neonatal intensive care unit (NICU) population.<h4>Study design</h4>We conducted a prospective evaluation of infants with suspected sepsis between September 2014 and February 2018; sepsis was defined as clinical concern prompting blood culture collection and antibiotic ... Read more >>

J Pediatr (The Journal of pediatrics)
[2020, 217:59-65.e1]

Cited: 2 times

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A Narrative Review of Analytics in Pediatric Cardiac Anesthesia and Critical Care Medicine.

Kelly L Grogan, Michael P Goldsmith, Aaron J Masino, Olivia Nelson, Fu-Chiang Tsui, Allan F Simpao,

Congenital heart disease (CHD) is one of the most common birth anomalies, and the care of children with CHD has improved over the past 4 decades. However, children with CHD who undergo general anesthesia remain at increased risk for morbidity and mortality. The proliferation of electronic health record systems and ... Read more >>

J Cardiothorac Vasc Anesth (Journal of cardiothoracic and vascular anesthesia)
[2020, 34(2):479-482]

Cited: 1 time

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Reply to comment on: "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts".

Anne Cocos, Alexander G Fiks, Aaron J Masino,

We appreciate the detailed review provided by Magge et al1 of our article, "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts." 2 In their letter, they present a subjective criticism that rests on concerns about our dataset composition and potential misinterpretation of ... Read more >>

J Am Med Inform Assoc (Journal of the American Medical Informatics Association : JAMIA)
[2019, 26(6):580-581]

Cited: 0 times

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Machine learning models for early sepsis recognition in the neonatal intensive care unit using readily available electronic health record data.

Aaron J Masino, Mary Catherine Harris, Daniel Forsyth, Svetlana Ostapenko, Lakshmi Srinivasan, Christopher P Bonafide, Fran Balamuth, Melissa Schmatz, Robert W Grundmeier,

<h4>Background</h4>Rapid antibiotic administration is known to improve sepsis outcomes, however early diagnosis remains challenging due to complex presentation. Our objective was to develop a model using readily available electronic health record (EHR) data capable of recognizing infant sepsis at least 4 hours prior to clinical recognition.<h4>Methods and findings</h4>We performed a ... Read more >>

PLoS One (PloS one)
[2019, 14(2):e0212665]

Cited: 13 times

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One Laryngospasm, 2 Realities: A Case Report Highlighting the Impact of Data Granularity on Post Hoc Analysis of Perioperative Events.

Allan F Simpao, Annie A Ma, Jonathan M Tan, Jack O Wasey, Aaron J Masino, Jorge A Gálvez,

We present the case of a laryngospasm event in a 21-month-old child in which the changes in pulse oximetry and end-tidal carbon dioxide were recorded by both our Anesthesia Information Management System and middleware medical device integration platform. When this case was analyzed retrospectively, we noted that the 2 systems ... Read more >>

A A Pract (A&A practice)
[2018, 11(11):315-317]

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Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts.

Anne Cocos, Alexander G Fiks, Aaron J Masino,

<h4>Objective</h4>Social media is an important pharmacovigilance data source for adverse drug reaction (ADR) identification. Human review of social media data is infeasible due to data quantity, thus natural language processing techniques are necessary. Social media includes informal vocabulary and irregular grammar, which challenge natural language processing methods. Our objective is ... Read more >>

J Am Med Inform Assoc (Journal of the American Medical Informatics Association : JAMIA)
[2017, 24(4):813-821]

Cited: 26 times

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Crowd control: Effectively utilizing unscreened crowd workers for biomedical data annotation.

Anne Cocos, Ting Qian, Chris Callison-Burch, Aaron J Masino,

Annotating unstructured texts in Electronic Health Records data is usually a necessary step for conducting machine learning research on such datasets. Manual annotation by domain experts provides data of the best quality, but has become increasingly impractical given the rapid increase in the volume of EHR data. In this article, ... Read more >>

J Biomed Inform (Journal of biomedical informatics)
[2017, 69:86-92]

Cited: 8 times

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Identification of Long Bone Fractures in Radiology Reports Using Natural Language Processing to support Healthcare Quality Improvement.

Robert W Grundmeier, Aaron J Masino, T Charles Casper, Jonathan M Dean, Jamie Bell, Rene Enriquez, Sara Deakyne, James M Chamberlain, Elizabeth R Alpern, ,

<h4>Background</h4>Important information to support healthcare quality improvement is often recorded in free text documents such as radiology reports. Natural language processing (NLP) methods may help extract this information, but these methods have rarely been applied outside the research laboratories where they were developed.<h4>Objective</h4>To implement and validate NLP tools to identify ... Read more >>

Appl Clin Inform (Applied clinical informatics)
[2016, 7(4):1051-1068]

Cited: 15 times

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Latent Patient Cluster Discovery for Robust Future Forecasting and New-Patient Generalization.

Ting Qian, Aaron J Masino,

Commonly referred to as predictive modeling, the use of machine learning and statistical methods to improve healthcare outcomes has recently gained traction in biomedical informatics research. Given the vast opportunities enabled by large Electronic Health Records (EHR) data and powerful resources for conducting predictive modeling, we argue that it is ... Read more >>

PLoS One (PloS one)
[2016, 11(9):e0162812]

Cited: 1 time

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Temporal bone radiology report classification using open source machine learning and natural langue processing libraries.

Aaron J Masino, Robert W Grundmeier, Jeffrey W Pennington, John A Germiller, E Bryan Crenshaw,

<h4>Background</h4>Radiology reports are a rich resource for biomedical research. Prior to utilization, trained experts must manually review reports to identify discrete outcomes. The Audiological and Genetic Database (AudGenDB) is a public, de-identified research database that contains over 16,000 radiology reports. Because the reports are unlabeled, it is difficult to select ... Read more >>

BMC Med Inform Decis Mak (BMC medical informatics and decision making)
[2016, 16:65]

Cited: 6 times

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