Zobrazeno 1 - 9
of 9
pro vyhledávání: '"J. Jojo Cheng"'
Predicting polycystic ovary syndrome with machine learning algorithms from electronic health records
Autor:
Zahra Zad, Victoria S. Jiang, Amber T. Wolf, Taiyao Wang, J. Jojo Cheng, Ioannis Ch. Paschalidis, Shruthi Mahalingaiah
Publikováno v:
Frontiers in Endocrinology, Vol 15 (2024)
IntroductionPredictive models have been used to aid early diagnosis of PCOS, though existing models are based on small sample sizes and limited to fertility clinic populations. We built a predictive model using machine learning algorithms based on an
Externí odkaz:
https://doaj.org/article/ffa4fb64bc2342699c3936c6e7be4430
Publikováno v:
ISEE Conference Abstracts. 2020
Autor:
Shruthi Mahalingaiah, J Jojo Cheng, Michael R Winter, Erika Rodriguez, Victoria Fruh, Anna Williams, MyMy Nguyen, Rashmi Madhavan, Pascaline Karanja, Jill MacRae, Sai Charan Konanki, Kevin J Lane, Ann Aschengrau
BACKGROUND Multimodal recruitment strategies are a novel way to increase diversity in research populations. However, these methods have not been previously applied to understanding the prevalence of menstrual disorders such as polycystic ovary syndro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::365a3ebbc8a6fb4cd812ac25c4e660f8
https://doi.org/10.2196/preprints.24716
https://doi.org/10.2196/preprints.24716
Autor:
Jill McRae, Ann Aschengrau, Pascaline Karanja, Kevin J Lane, Erika Rodriguez, MyMy Nguyen, Shruthi Mahalingaiah, Michael Winter, Sai Charan Konanki, Anna Larson Williams, J. Jojo Cheng, Victoria Fruh, Rashmi Madhavan
BackgroundMultimodal recruitment strategies are a novel way to increase diversity of research populations. However, these methods have not been previously applied to understanding the prevalence of menstrual disorders such as polycystic ovary syndrom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5af4e74b360d13a6fc3e897a6b5848c4
https://doi.org/10.1101/2020.06.29.20142778
https://doi.org/10.1101/2020.06.29.20142778
Publikováno v:
Fertility Research and Practice
Fertility Research and Practice, Vol 6, Iss 1, Pp 1-10 (2020)
Fertility Research and Practice, Vol 6, Iss 1, Pp 1-10 (2020)
Background In large population-based studies, there is a lack of existing survey instruments designed to ascertain menstrual cycle characteristics and androgen excess status including hirsutism, alopecia, and acne. Our objective was to cognitively te
Context: In large population-based studies, there are a lack of existing questionnaires designed to ascertain menstrual cycle characteristics and tools to assess androgen excess including hirsutism, alopecia, and acne. Objective: Our objective was to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf2b6798e4d79a7dcb34868d5c9cb464
https://doi.org/10.1101/2020.03.03.20030676
https://doi.org/10.1101/2020.03.03.20030676
Publikováno v:
Current Epidemiology Reports. 5:197-204
Air pollution is widely known to affect human cardiopulmonary health, but only recently has research begun to focus on understanding the association between ambient air pollution and reproductive health and gynecologic disease incidence. In this arti
Multimodal Recruitment to Study Ovulation and Menstruation Health: Internet-Based Survey Pilot Study
Autor:
Shruthi Mahalingaiah, Ann Aschengrau, J. Jojo Cheng, Anna Larson Williams, Michael Winter, Kevin J Lane, Jill MacRae, Sai Charan Konanki, MyMy Nguyen, Pascaline Karanja, Erika Rodriguez, Rashmi Madhavan, Victoria Fruh
Publikováno v:
Journal of Medical Internet Research
Journal of Medical Internet Research, Vol 23, Iss 4, p e24716 (2021)
Journal of Medical Internet Research, Vol 23, Iss 4, p e24716 (2021)
Background Multimodal recruitment strategies are a novel way to increase diversity in research populations. However, these methods have not been previously applied to understanding the prevalence of menstrual disorders such as polycystic ovary syndro
Autor:
Shruthi Mahalingaiah, J. Jojo Cheng, Kathryn L. Lunetta, Joanne M. Murabito, Fangui Sun, Erika T. Chow
Publikováno v:
Fertility Research and Practice
Fertility Research and Practice, Vol 3, Iss 1, Pp 1-7 (2017)
Fertility Research and Practice, Vol 3, Iss 1, Pp 1-7 (2017)
Background Amongst women with certain types of ovulatory disorder infertility, the studies are conflicting whether there is an increased risk of long-term cardiovascular disease risk. This paper evaluates the associations of several CVD risk factors