Roxana Daneshjou
Roxana Daneshjou
MD/Ph.D, Dermatology Clinical Scholar, Stanford University
Verified email at
Cited by
Cited by
Data-driven prediction of drug effects and interactions
NP Tatonetti, PP Ye, R Daneshjou, RB Altman
Science translational medicine 4 (125), 125ra31-125ra31, 2012
Bioinformatics challenges for personalized medicine
GH Fernald, E Capriotti, R Daneshjou, KJ Karczewski, RB Altman
Bioinformatics 27 (13), 1741-1748, 2011
Genetic variants associated with warfarin dose in African-American individuals: a genome-wide association study
MA Perera, LH Cavallari, NA Limdi, ER Gamazon, A Konkashbaev, ...
The Lancet 382 (9894), 790-796, 2013
How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals
E Wu, K Wu, R Daneshjou, D Ouyang, DE Ho, J Zou
Nature Medicine 27 (4), 582-584, 2021
Chapter 7: pharmacogenomics
KJ Karczewski, R Daneshjou, RB Altman
PLoS computational biology 8 (12), e1002817, 2012
Genetic variant in folate homeostasis is associated with lower warfarin dose in African Americans
R Daneshjou, ER Gamazon, B Burkley, LH Cavallari, JA Johnson, ...
Blood, The Journal of the American Society of Hematology 124 (14), 2298-2305, 2014
Targeted exon capture and sequencing in sporadic amyotrophic lateral sclerosis
J Couthouis, AR Raphael, R Daneshjou, AD Gitler
PLoS genetics 10 (10), e1004704, 2014
Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges
R Daneshjou, Y Wang, Y Bromberg, S Bovo, PL Martelli, G Babbi, ...
Human mutation 38 (9), 1182-1192, 2017
PharmGKB summary: very important pharmacogene information for CYP4F2
ML Alvarellos, K Sangkuhl, R Daneshjou, M Whirl-Carrillo, RB Altman, ...
Pharmacogenetics and genomics 25 (1), 41, 2015
Pathway analysis of genome-wide data improves warfarin dose prediction
R Daneshjou, NP Tatonetti, KJ Karczewski, H Sagreiya, S Bourgeois, ...
BMC genomics 14 (3), 1-12, 2013
Lack of transparency and potential bias in artificial intelligence data sets and algorithms: a scoping review
R Daneshjou, MP Smith, MD Sun, V Rotemberg, J Zou
JAMA dermatology 157 (11), 1362-1369, 2021
Pharmacogenomics and big genomic data: from lab to clinic and back again
A Lavertu, G McInnes, R Daneshjou, M Whirl-Carrillo, TE Klein, ...
Human molecular genetics 27 (R1), R72-R78, 2018
Checklist for evaluation of image-based artificial intelligence reports in dermatology: CLEAR Derm consensus guidelines from the International Skin Imaging Collaboration …
R Daneshjou, C Barata, B Betz-Stablein, ME Celebi, N Codella, ...
JAMA dermatology 158 (1), 90-96, 2022
Twitter journal clubs: medical education in the era of social media
R Daneshjou, AS Adamson
JAMA dermatology 156 (7), 729-730, 2020
Pernio-like eruption associated with COVID-19 in skin of color
R Daneshjou, J Rana, M Dickman, JM Yost, A Chiou, J Ko
JAAD Case Reports 6 (9), 892-897, 2020
Genome-wide meta-analysis identifies eight new susceptibility loci for cutaneous squamous cell carcinoma
KY Sarin, Y Lin, R Daneshjou, A Ziyatdinov, G Thorleifsson, A Rubin, ...
Nature communications 11 (1), 1-8, 2020
PATH-SCAN: a reporting tool for identifying clinically actionable variants
R Daneshjou, Z Zappala, K Kukurba, SM Boyle, KE Ormond, TE Klein, ...
Biocomputing 2014, 229-240, 2014
How to evaluate deep learning for cancer diagnostics–factors and recommendations
R Daneshjou, B He, D Ouyang, JY Zou
Biochimica et Biophysica Acta (BBA)-Reviews on Cancer 1875 (2), 188515, 2021
Clinical photography in skin of colour: tips and best practices
JC Lester, L Clark Jr, E Linos, R Daneshjou
British Journal of Dermatology 184 (6), 1177-1179, 2021
TrueImage: a machine learning algorithm to improve the quality of telehealth photos
K Vodrahalli, R Daneshjou, RA Novoa, A Chiou, JM Ko, J Zou
BIOCOMPUTING 2021: Proceedings of the Pacific Symposium, 220-231, 2020
The system can't perform the operation now. Try again later.
Articles 1–20