Welcome to the Fertility and Health Informatics lab. We are housed at the Institute for Biomedical Informatics in the Department of Biostatistics, Epidemiology & Informatics (DBEI), of the Perelman School of Medicine, University of Pennsylvania. This lab is headed by Dr. Mary Regina Boland. Dr. Boland is a longtime member of the American Medical Informatics Association and a member of the American Society for Reproductive Medicine. She also holds memberships at the American Society for Clinical Pharmacology & Therapeutics and the American Geophysical Union
Our mission is to improve understanding of fertility and overall health using informatics methods. We specialize in developing algorithms that explore the effects of prenatal and perinatal exposures on later risk of disease. This includes exploring birth season relationships (as a proxy for seasonal exposures) and their impact on a number of diseases including cardiovascular, neurological, respiratory and female reproductive conditions.
Female fertility is a complex phenotype composed of numerous other phenotypes (e.g., endometriosis, polycystic ovary syndrome, ectopic pregnancy) and for this reason specialized informatics methods are required to extract and quantify female fertility. We also explore the role of pharmacologics on female fertility and adverse pregnancy outcomes, this includes pharmacologics that are not direct hormonal modulators, but that effect fertility through indirect mechanisms.
On the informatics-side, our work focuses on developing novel and interesting data mining methods that integrate data from electronic health records, observational health data and genetic data. On the clinical side, our work focuses on the relationship between environment and disease, especially during the prenatal / perinatal period. Because developmental effects due to the environment can be hard to study in adult populations, I use birth-related data (such as birth month) as a proxy for the environment at birth (perinatal) and prior to birth (prenatal).
We are always interested in any female fertility related questions that could use informatics methods to solve. In addition, we explore many other diseases that are birth season dependent as these are important for a wholistic approach to human health. Feel free to contact us!
Our mission is to improve understanding of fertility and overall health using informatics methods. We specialize in developing algorithms that explore the effects of prenatal and perinatal exposures on later risk of disease. This includes exploring birth season relationships (as a proxy for seasonal exposures) and their impact on a number of diseases including cardiovascular, neurological, respiratory and female reproductive conditions.
Female fertility is a complex phenotype composed of numerous other phenotypes (e.g., endometriosis, polycystic ovary syndrome, ectopic pregnancy) and for this reason specialized informatics methods are required to extract and quantify female fertility. We also explore the role of pharmacologics on female fertility and adverse pregnancy outcomes, this includes pharmacologics that are not direct hormonal modulators, but that effect fertility through indirect mechanisms.
On the informatics-side, our work focuses on developing novel and interesting data mining methods that integrate data from electronic health records, observational health data and genetic data. On the clinical side, our work focuses on the relationship between environment and disease, especially during the prenatal / perinatal period. Because developmental effects due to the environment can be hard to study in adult populations, I use birth-related data (such as birth month) as a proxy for the environment at birth (perinatal) and prior to birth (prenatal).
We are always interested in any female fertility related questions that could use informatics methods to solve. In addition, we explore many other diseases that are birth season dependent as these are important for a wholistic approach to human health. Feel free to contact us!