Mary Regina Boland, MA, MPhil, PhD, FAMIA 

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Welcome to my homepage. I am currently a tenure-track Assistant Professor of Informatics at the University of Pennsylvania. I am a  Basic Science representative (elected) to the Medical Faculty Senate at the University of Pennsylvania currently, my term is from 2019-2021. I was just elected to be a Fellow of the American Medical Informatics Association (FAMIA) in May 2020. I am on the editorial board of the Journal of the American Medical Informatics Association for a term of 2-years (2020-2022). 
I develop novel informatics methods to study the effects of environmental pollutants, genetics and social determinants of health on clinical outcomes. I focus on prenatal and perinatal exposures and disease outcomes, including fertility-related outcomes and I run the Fertility and Health Informatics Lab at the University of Pennsylvania. My UPenn lab website is located here

Recently received a 16k pilot grant from the Penn Injury Science Center (PISC)!
Information on my work can be found at the UPenn lab website here or  Fertility and Health Informatics Lab website.

I am a member of the Department of Biomedical and Health Informatics (DBHi) at the Children's Hospital of Philadelphia (CHOP), the Center for Excellence in Environmental Toxicology (CEET) at the University of Pennsylvania and the Leonard Davis Institute of Health Economics, Wharton School, University of Pennsylvania. 

I have written over 50 peer-reviewed papers (for full list see here). 
Recently Accepted and Published Papers (2019-2020) are shown below, organized by theme!!

Environmental Exposures
1. O Wetherbee, J Meeker, C DeVoto, T Penning, J Moore, MR Boland. WellExplorer: An Integrative Resource Linking Hydraulic Fracturing Chemicals with Targeted Proteins, Hormonal Pathways and Geographic Location. Database. 2020; In press.
2. S Canelon, MR Boland. A Systematic Literature Review on Factors Affecting the Timing of Menarche: Potential for Climate Change to Impact Women's Health. International Journal of Environmental Research and Public Health. 2020. In press
4. R Bai, GE Moran, J Antonelli, Y Chen*, MR Boland*. Spike-and-Slab Group Lassos for Grouped Regression and Sparse Generalized Additive Models. Journal of American Statistical Association (JASA) Applications. 2020; In Press. *Joint Senior Author
5. MR Boland, NP Tatonetti Attention Deficit–Hyperactivity Disorder and Month of School Enrollment. NEJM 2019;380(7):692-693.

Pregnancy and Pharmacovigilance / Medication Safety
1. L Davidson, MR Boland. Towards Deep Phenotyping Pregnancy: A Systematic Review on Artificial Intelligence and Machine Learning Methods to Improve Pregnancy Outcomes. Briefings in Bioinformatics. 2020; In press
2. S Canelon, HH Burris, LD Levine, MR Boland. Development and Evaluation of MADDIE: Method to Acquire Delivery Date Information from Electronic Health Records. International Journal of Medical Informatics. 2020. In press.

3. L Davidson, MR Boland. Enabling Pregnant Women and their Physicians to Make Informed Medication Decisions Using Artificial Intelligence. Journal of Pharmacokinetics and Pharmacodynamics 2020; In Press.

4. L Davidson, MR Boland. Comparative Analysis and Evaluation of State-of-the-Art Medication Mapping Tools to Transform a Local Medication Terminology to RxNorm. AMIA Informatics Summit 2020, Houston, Tx, USA (full paper). In press.

Disambiguating Meaning from Clinical Notes and Informatics Methods

1. A Kashyap, H Burris, C Callison-Burch, MR Boland. The CLASSE GATOR (CLinical Acronym SenSE disambiGuATOR): A Method for Predicting Acronym Sense from Neonatal Clinical Notes. International Journal of Medical Informatics. 2020. In press.

2. MR Boland, ML Casal, M Kraus, AR Gelzer. Applied Veterinary Informatics: Development of a Semantic and Domain-Specific Method to Construct a Canine Data Repository. Scientific Reports. 2019; 9: 18641.

3. MR Boland, S Alar-Gupta, L Levine, P Gabriel, G Gonzalez. Disease Associations Depend on Visit Type: Results from a Visit-Wide Association Study. BioData Mining. 2019; In press.
4. R Duan, C Luo, MJ Schuemie, J Tong, JC Liang, HH Chang, MR Boland, J Bian, H Xu, JH Holmes, CB Forrest, SC Morton, JA Berlin, JH Moore, KB Mahoney, Y Chen. Learning from local to global-an efficient distributed algorithm for modeling time-to-event data. J Am Med Inform Assoc. 2020. In press
5. J Moore, MR Boland, P Camara, G Gonzalez, B Himes, D Mowery, M Ritchie, L Shen, R Urbanowicz, J Holmes. Preparing next generation scientists for biomedical big data: Artificial intelligence approaches. Personalized Medicine. 2019
6. R Duan, MR Boland*, JH Moore, Y Chen. ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites. In Press at 2019 Pacific Symposium on Biocomputing. *Equal-contribution first-author

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