scholarly journals Human gene and disease associations for clinical‐genomics and precision medicine research

2020 ◽  
Vol 10 (1) ◽  
pp. 297-318 ◽  
Author(s):  
Zeeshan Ahmed ◽  
Saman Zeeshan ◽  
Dinesh Mendhe ◽  
XinQi Dong
Keyword(s):  
Precision Medicine ◽  
Human Gene ◽  
Clinical Genomics ◽  
Medicine Research ◽  
Disease Associations ◽  
Precision Medicine Research

Increasing inclusivity in precision medicine research: Views of individuals who are deaf and hard of hearing

2021 ◽  
Author(s):  
Diana C. Garofalo ◽  
Howard A. Rosenblum ◽  
Yuan Zhang ◽  
Ying Chen ◽  
Paul S. Appelbaum ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Hard Of Hearing ◽  
Medicine Research ◽  
Precision Medicine Research

scholarly journals Machine Learning Methods for Precision Medicine Research Designed to Reduce Health Disparities: A Structured Tutorial

2020 ◽  
Vol 30 (Suppl 1) ◽  
pp. 217-228 ◽  
Author(s):  
Sanjay Basu ◽  
James H. Faghmous ◽  
Patrick Doupe
Keyword(s):  
Machine Learning ◽  
Health Disparities ◽  
Precision Medicine ◽  
Learning Approaches ◽  
Learning Methods ◽  
Medicine Research ◽  
Machine Learning Methods ◽  
Box Models ◽  
Precision Medicine Research ◽  
Key Terms

  Precision medicine research designed to reduce health disparities often involves studying multi-level datasets to understand how diseases manifest disproportionately in one group over another, and how scarce health care resources can be directed precisely to those most at risk for disease. In this article, we provide a structured tutorial for medical and public health research­ers on the application of machine learning methods to conduct precision medicine research designed to reduce health dispari­ties. We review key terms and concepts for understanding machine learning papers, including supervised and unsupervised learning, regularization, cross-validation, bagging, and boosting. Metrics are reviewed for evaluating machine learners and major families of learning approaches, including tree-based learning, deep learning, and ensemble learning. We highlight the advan­tages and disadvantages of different learning approaches, describe strategies for interpret­ing “black box” models, and demonstrate the application of common methods in an example dataset with open-source statistical code in R.Ethn Dis. 2020;30(Suppl 1):217-228; doi:10.18865/ed.30.S1.217

scholarly journals Disability inclusion in precision medicine research: a first national survey

2019 ◽  
Vol 21 (10) ◽  
pp. 2319-2327 ◽  
Author(s):  
Maya Sabatello ◽  
Ying Chen ◽  
Yuan Zhang ◽  
Paul S. Appelbaum
Keyword(s):  
Precision Medicine ◽  
National Survey ◽  
Medicine Research ◽  
Precision Medicine Research

scholarly journals Conducting Precision Medicine Research with African Americans

PLoS ONE ◽  
2016 ◽  
Vol 11 (7) ◽  
pp. e0154850 ◽  
Author(s):  
Chanita Hughes Halbert ◽  
Jasmine McDonald ◽  
Susan Vadaparampil ◽  
LaShanta Rice ◽  
Melanie Jefferson
Keyword(s):  
African Americans ◽  
Precision Medicine ◽  
Medicine Research ◽  
Precision Medicine Research

scholarly journals A roadmap for precision medicine research recruitment: empirical assessment of the public's willingness to participate

2020 ◽  
Vol 17 (5) ◽  
pp. 345-359
Author(s):  
Kelsey Moriarty ◽  
Susan M Wolf ◽  
Patricia M Veach ◽  
Bonnie LeRoy ◽  
Ian M MacFarlane ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Recruitment Strategies ◽  
Graduate Degree ◽  
Willingness To Participate ◽  
Family Participation ◽  
Research Recruitment ◽  
Medicine Research ◽  
Electronic Survey ◽  
Survey Results ◽  
Precision Medicine Research

Aim: Precision medicine research recruitment poses challenges. To better understand factors impacting recruitment, this study assessed hypothetical willingness, public opinions of and familiarity with precision medicine research. Materials & methods: Adult attendees (n = 942) at the 2017 Minnesota State Fair completed an electronic survey. Results: Few respondents had heard of ‘precision medicine’ (18%), and familiarity came mostly from media (43%). Fifty-six percent expressed hypothetical willingness to participate in precision medicine research. Significant predictors of willingness were: comfort with unconditional research; perceiving precision medicine research as beneficial, trustworthy and confidential; having a graduate degree; comfort with self- but not family-participation; and familiarity with precision/personalized medicine. Conclusion: This study identified predictors of hypothetical willingness to participate in precision medicine research. Alternative recruitment strategies are needed.

scholarly journals Thought Leader Comparisons of Risks in Precision Medicine Research

2020 ◽  
Vol 42 (6) ◽  
pp. 35-40
Author(s):  
Laura M. Beskow ◽  
Catherine M. Hammack‐Aviran ◽  
Kathleen M. Brelsford
Keyword(s):  
Precision Medicine ◽  
Medicine Research ◽  
Thought Leader ◽  
Precision Medicine Research
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