Survey, Qualitative & Mixed Methods

View BHDSC Seminar: “Toward a Generalized Model of Biomedical Query Mediation to Improve Electronic Health Record Data Retrieval” Event Information
Seminars & Workshops
BHDSC Seminar: “Toward a Generalized Model of Biomedical Query Mediation to Improve Electronic Health Record Data Retrieval”
Feb 28 , 2024

The Biomedical and Health Data Sciences Collaborative (BHDSC), a cross-disciplinary group formed by Tufts Clinical and Translational Science Institute (CTSI) and Institute for Clinical Research and Health Policy Studies (ICRHPS) at Tufts Medical Center, invites you to attend a virtual seminar on Wednesday, February 28 from 2:00PM-3:00PM.

Dr. Gregory W. Hruby will give a talk titled ” Toward a Generalized Model of Biomedical Query Mediation to Improve Electronic Health Record Data Retrieval.”

Abstract

The EHR serves as a vital resource for medical knowledge discovery, demanding both medical and technical expertise for data interrogation. Biomedical query mediation (BQM) is the process where medical researchers collaborate with query analysts to translate information needs into EHR queries. The absence of a BQM standard leads to varied practices, potentially affecting dataset accuracy. This work enhances understanding of BQM through three studies: 1) content analysis of the BQM process, 2) cognitive task analysis for workflow, and 3) development of a concept schema for comprehensive EHR data needs.

Speaker Bio

Gregory W. Hruby, a Clinical Research Scientist with a PhD in Biomedical Informatics from Columbia University, is dedicated to advancing clinical care value initiatives. With a solid foundation in qualitative and quantitative methods, he specializes in extracting insights from complex communication processes between medical data seekers and electronic health record data analysts. His expertise includes extensive knowledge of electronic healthcare data, spanning EHR/ERP systems and various data terminologies.

Details

Wednesday, February 28, 2024
2:00PM-3:00PM EST

To attend virtually, click here.

Contact

Please contact Anastasia Gurinovich and Ellaina Reed if you have any questions. Feel free to pass on to others who may be interested.

View BHDSC Seminar: “Using Google search data for localized flu tracking” Event Information
Seminars & Workshops
BHDSC Seminar: “Using Google search data for localized flu tracking”
Jan 24 , 2024

The Biomedical and Health Data Sciences Collaborative (BHDSC), a cross-disciplinary group formed by the Tufts Clinical and Translational Science Institute (CTSI) and Institute for Clinical Research and Health Policy Studies (ICRHPS) at Tufts Medical Center, invites you to attend an in-person seminar (with a virtual option) on Wednesday, January 24 at 2:00PM at 35 Kneeland Street, 8th Floor Conference room.

Dr. Shaoyang Ning will give a talk titled “Using Google search data for localized flu tracking.”

Abstract

Big data from the Internet has great potential to track social and economic events at multiple geographical levels. Focusing on localized (regional, state-level) tracking the seasonal influenza epidemics within U.S., I will introduce a statistical model that efficiently combines publicly available Google search data at different geographical resolutions with traditional influenza surveillance data from the Centers for Disease Control and Prevention. Our method outperforms time-series-based influenza tracking methods. Our model is robust and easy to implement, with the flexibility to incorporate additional information from other sources and/or resolutions, making it generally applicable to tracking other social, economic or public health events (such as COVID-19) at the regional or local level.

Speaker Bio

Shaoyang Ning is an Assistant Professor of Statistics in the Department of Mathematics & Statistics at Williams College. He received my Ph.D. in Statistics from Harvard in 2018 and his B.S. in Probability and Statistics from Peking University, China in 2013. His research focuses on the study and design of statistical methods for integrative data analysis, in particular, to address the challenges of increasing complexity and connectivity arising from “Big Data”. He is interested in innovating statistical methods that efficiently integrate multi-source, multi-resolution information to solve real-life problems. Instances include tracking flu activities (and other infectious diseases) with Google search data and predicting cancer-targeting drugs with high-throughput multi-omics data.

Details

Wednesday, January 24, 2024
2:00PM-3:00PM EST

To attend virtually, click here.

Contact

Please contact Anastasia Gurinovich and Ellaina Reed if you have any questions. Feel free to pass on to others who may be interested.

View BHDSC Seminar: “Integrating post sequencing workflows and statistical approaches to improve the robustness of microbial community data analyses” Event Information
Seminars & Workshops
BHDSC Seminar: “Integrating post sequencing workflows and statistical approaches to improve the robustness of microbial community data analyses”
Nov 15 , 2023

The Biomedical and Health Data Sciences Collaborative (BHDSC), a cross-disciplinary group formed by the Tufts Clinical and Translational Science Institute (CTSI) and Institute for Clinical Research and Health Policy Studies (ICRHPS) at Tufts Medical Center, invites you to attend an in-person seminar (with a virtual option) at 35 Kneeland Street, 8th Floor Conference room.

Dr. Jacob Nearing will give a talk titled “Integrating post sequencing workflows and statistical approaches to improve the robustness of microbial community data analyses”.

Abstract

Modern day sequencing technology has allowed researchers to take vast surveys of the various microbes living within numerous environments including the human body, ocean, and soil. Through this work we have found that these microbial communities, termed the microbiome, can play significant roles in their environment’s ecosystem. Yet, while various microbe(s) have been associated with numerous phenotypes such as host health, these results are often not reproducible across studies. There are many reasons as to why this may be the case including the difficulty in matching results between differing sequencing technologies such as 16S rRNA gene sequencing and shotgun metagenomic sequencing or the use of differing statistical models during data analysis. Both of which can result in differing biological conclusions from the same underlying samples. In this presentation, I will highlight my recent research on developing a tool to help address the gap between 16S and shotgun sequencing using phylogenetic placement and the use of uncertainty in difficult to assign taxonomic labels, to provide more clarity during downstream analysis. With the final goal of creating microbial profiles that have higher agreement between differing sequencing technologies. In addition,  I will  present another part of work on evaluating how differing commonly used statistical approaches in microbiome data analysis can result in different biological interpretations. Highlighting the need for more robust approaches to modeling microbiome data in the future.

Speaker Bio

Dr. Jacob Nearing is a postdoctoral fellow in the department of biostatistics at the Harvard T.H. Chan School of Public Health. Under the supervision of Dr. Curtis Huttenhower, he focuses on improving microbiome data analysis through the creation of new bioinformatic tools and evaluating those already present in the current literature. He has expertise in microbiome data analysis, microbiology, and bioinformatic research. During his PhD at Dalhousie University in Halifax, Nova Scotia, he received numerous scholarships to fund his work on the oral microbiome and cancer. During 2022, Nature Communications highlighted his work on microbiome differential abundance analysis as one of the top 25 most downloaded works published in the biology section for that year.

Details

Wednesday, November 15, 2023
2:00PM-3:00PM EST

To attend virtually, click here.

Contact

Please contact Anastasia Gurinovich  and Ellaina Reed if you have any questions. Feel free to pass on to others who may be interested.