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Yale University

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Full-Text Articles in Medicine and Health Sciences

Saving Software And Using Emulation To Reproduce Computationally Dependent Research Results, Euan Cochrane, Limor Peer, Ethan Gates, Seth Anderson Dec 2019

Saving Software And Using Emulation To Reproduce Computationally Dependent Research Results, Euan Cochrane, Limor Peer, Ethan Gates, Seth Anderson

Yale Day of Data

Using digital data necessarily involves software. How do institutions think about software in the context of the long-term usability of their data assets? How do they address usability challenges uniquely posed by software such as, license restrictions, legacy software, code rot, and dependencies? These questions are germane to the agenda set forth by the FAIR principles. At Yale University, a team in the Library is looking into the application of a novel approach to emulation as a potential solution. In this presentation, we will outline the work of the Emulation as a Service Infrastructure (EaaSI) program, discuss our plans for …


Gene Co-Expression Networks Analysis Reveal Novel Molecular Endotypes In Alpha-1 Antitrypsin Deficiency, Jen-Hwa Chu, Wenlan Zang Jan 2019

Gene Co-Expression Networks Analysis Reveal Novel Molecular Endotypes In Alpha-1 Antitrypsin Deficiency, Jen-Hwa Chu, Wenlan Zang

Yale Day of Data

Rationale:Alpha-1 antitrypsin deficiency (AATD) is a genetic condition that predisposes to early onset pulmonary emphysema and airways obstruction. The exact mechanism through which AATD leads to lung disease is incompletely understood.

Objectives: To investigate the effect of AAT genotype and augmentation therapy on bronchoalveolar lavage (BAL) and peripheral blood mononuclear cells (PBMC) transcriptome, while examining the link between gene expression profiles, and clinical features of AATD.

Methods: We performed RNA-Seq on RNA extracted from BAL and PBMC on samples obtained from 89 AATD patients enrolled in the Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study. Differential …


Non-Invasive Analysis Of The Sputum Transcriptome Discriminates Clinical Phenotypes Of Asthma, Xiting Yan Jan 2019

Non-Invasive Analysis Of The Sputum Transcriptome Discriminates Clinical Phenotypes Of Asthma, Xiting Yan

Yale Day of Data

Whole transcriptome wide gene expression profiles in the sputum and circulation from 100 asthma patients were measured using the Affymetrix HuGene 1.0ST arrays. Unsupervised clustering analysis based on pathways from KEGG were used to identify TEA clusters of patients from the sputum gene expression profiles. The identified TEA clusters have significantly different pre-bronchodilator FEV1, bronchodilator responsiveness, exhaled nitric oxide levels, history of hospitalization for asthma and history of intubation. Evaluation of TEA clusters in children from Asthma BRIDGE cohort confirmed the identified differences in intubation and hospitalization. Furthermore, evaluation of the TH2 gene signatures suggested a much lower prevalence of …


A Machine Learning Approach To Post-Market Surveillance Of Medical Devices, Jonathan Bates, Shu-Xia Li, Craig Parzynski, Ronald Coifman, Harlan Krumholz, Joseph Ross Sep 2015

A Machine Learning Approach To Post-Market Surveillance Of Medical Devices, Jonathan Bates, Shu-Xia Li, Craig Parzynski, Ronald Coifman, Harlan Krumholz, Joseph Ross

Yale Day of Data

Post-market surveillance is a collection of processes and activities used by product manufacturers and regulators, such as the U.S. Food and Drug Administration (FDA) to monitor the safety and effectiveness of medical devices once they are available for use “on the market”. These activities are designed to generate information to identify poorly performing devices and other safety problems, accurately characterize real-world device performance and clinical outcomes, and facilitate the development of new devices, or new uses for existing devices. Typically, a device is monitored by comparing adverse events in the exposed population to a matched unexposed population. This research considers …


Using Graphs To Characterize Nationwide Physician Referral Networks, Ding Tong, Shu-Xia Li, Isuru Ranasinghe, Sudhakar Nuti, Hongyu Zhao, Harlan Krumholz Sep 2014

Using Graphs To Characterize Nationwide Physician Referral Networks, Ding Tong, Shu-Xia Li, Isuru Ranasinghe, Sudhakar Nuti, Hongyu Zhao, Harlan Krumholz

Yale Day of Data

AIM:

Evaluating physician referral network characteristics can help to understand how physicians and hospitals interact to provide patient services within the US healthcare system and ultimately how this may influence patient outcomes.

METHOD:

We used the 2012-2013 national Physician Referral data from the Centers for Medicare & Medicaid Services (CMS), which consists of 73,071,804 pairs of referrals from one health provider to another in calendar year 2012 and the first two quarters of year 2013 within 30 days of care. These referrals are from 642,144 national-wide physicians and 4,811 hospitals. We obtained information for each provider, physician or hospital, from …


Stratified Meta-Analysis To Examine Data Biases In Lung Cancer Studies Of Refinery Workers, Sherman Selix Sep 2014

Stratified Meta-Analysis To Examine Data Biases In Lung Cancer Studies Of Refinery Workers, Sherman Selix

Yale Day of Data

Petroleum refineries employ a variety of workers who historically experienced different potentials for asbestos exposure depending on job tasks. Associations between petroleum refinery work and lung cancer related to occupational asbestos exposure have been quantified among various locations, corporations, and time periods. To combine the data from several individual refinery studies and examine an overall effect, a systematic review and stratified meta-analysis was employed. Using set search terms among four databases, 112 potential publications were identified, of which 29 qualified for meta-analysis. Risk estimates and confidence intervals were extracted from these publications to construct four separate datasets. Inverse variance weighting …