| Original language | English (US) |
|---|---|
| Pages (from-to) | 983-988 |
| Number of pages | 6 |
| Journal | Pharmacogenomics |
| Volume | 20 |
| Issue number | 14 |
| DOIs | |
| State | Published - 2019 |
Keywords
- antidepressants
- artificial intelligence
- clinical response
- depression
- major depression
ASJC Scopus subject areas
- Molecular Medicine
- Genetics
- Pharmacology
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Integration of machine learning and pharmacogenomic biomarkers for predicting response to antidepressant treatment : Can computational intelligence be used to augment clinical assessments? / Athreya, Arjun P.; Iyer, Ravishankar; Wang, Liewei et al.
In: Pharmacogenomics, Vol. 20, No. 14, 2019, p. 983-988.Research output: Contribution to journal › Review article › peer-review
}
TY - JOUR
T1 - Integration of machine learning and pharmacogenomic biomarkers for predicting response to antidepressant treatment
T2 - Can computational intelligence be used to augment clinical assessments?
AU - Athreya, Arjun P.
AU - Iyer, Ravishankar
AU - Wang, Liewei
AU - Weinshilboum, Richard M.
AU - Bobo, William V.
N1 - Funding Information: L Wang and RM Weinshilboum are co-founders and stockholders in OneOme LLC. WV Bobo's research has been supported by the National Institute of Mental Health, the Agency for Healthcare Research & Quality, and the Mayo Foundation for Medical Education and Research. He has contributed chapters to UpToDate concerning the use of antidepressants and atypical antipsychotic drugs for treating adults with bipolar major depression. All others declared no competing interests for this work. This material is based upon work partially supported by a Mayo Clinic and Illinois Alliance Fellowship for Technology-Based Healthcare Research; a CompGen Fellowship; an IBM Faculty Award; the National Science Foundation (NSF) under Grant Number CNS 13-37732; the National Institutes of Health (NIH) under Grant Numbers U19 GM61388, R01 GM28157, RC2 GM092729, R24 GM078233, RC2 GM092729 and T32 GM072474; and the Mayo Clinic Center for Individualized Medicine. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF or the NIH. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. Funding Information: L Wang and RM Weinshilboum are co-founders and stockholders in OneOme LLC. WV Bobo’s research has been supported by the National Institute of Mental Health, the Agency for Healthcare Research & Quality, and the Mayo Foundation for Medical Education and Research. He has contributed chapters to UpToDate concerning the use of antidepressants and atypical antipsychotic drugs for treating adults with bipolar major depression. All others declared no competing interests for this work. This material is based upon work partially supported by a Mayo Clinic and Illinois Alliance Fellowship for Technology-Based Healthcare Research; a CompGen Fellowship; an IBM Faculty Award; the National Science Foundation (NSF) under Grant Number CNS 13-37732; the National Institutes of Health (NIH) under Grant Numbers U19 GM61388, R01 GM28157, RC2 GM092729, R24 GM078233, RC2 GM092729 and T32 GM072474; and the Mayo Clinic Center for Individualized Medicine. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF or the NIH. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.
PY - 2019
Y1 - 2019
KW - antidepressants
KW - artificial intelligence
KW - clinical response
KW - depression
KW - major depression
UR - http://www.scopus.com/inward/record.url?scp=85072712741&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072712741&partnerID=8YFLogxK
U2 - 10.2217/pgs-2019-0119
DO - 10.2217/pgs-2019-0119
M3 - Review article
C2 - 31559920
AN - SCOPUS:85072712741
VL - 20
SP - 983
EP - 988
JO - Pharmacogenomics
JF - Pharmacogenomics
SN - 1462-2416
IS - 14
ER -