Zobrazeno 1 - 10
of 1 710
pro vyhledávání: '"DiPietro P"'
Autor:
Laura Dipietro, Uri Eden, Seth Elkin-Frankston, Mirret M. El-Hagrassy, Deniz Doruk Camsari, Ciro Ramos-Estebanez, Felipe Fregni, Timothy Wagner
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-28 (2024)
Abstract One of the key challenges in Big Data for clinical research and healthcare is how to integrate new sources of data, whose relation to disease processes are often not well understood, with multiple classical clinical measurements that have be
Externí odkaz:
https://doaj.org/article/736f04c60d03428bb57ee756d6457e66
Autor:
May Barakat, Chen Han, Lin Chen, Brian P. David, Junhe Shi, Angela Xu, Kornelia J. Skowron, Tatum Johnson, Reginald A. Woods, Aparna Ankireddy, Sekhar P. Reddy, Terry W. Moore, Luisa A. DiPietro
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-24 (2024)
Abstract The transcription factor NRF2 plays an important role in many biological processes and is a promising therapeutic target for many disease states. NRF2 is highly expressed in the skin and is known to play a critical role in diabetic wound hea
Externí odkaz:
https://doaj.org/article/2bc85f20295a4c28a88558c8a966f094
Autor:
Madondo, Malvern, Azmat, Muneeza, Dipietro, Kelsey, Horesh, Raya, Jacobs, Michael, Bawa, Arun, Srinivasan, Raghavan, O'Donncha, Fearghal
Crop management involves a series of critical, interdependent decisions or actions in a complex and highly uncertain environment, which exhibit distinct spatial and temporal variations. Managing resource inputs such as fertilizer and irrigation in th
Externí odkaz:
http://arxiv.org/abs/2302.04988
Autor:
Azmat, Muneeza, Madondo, Malvern, Dipietro, Kelsey, Horesh, Raya, Bawa, Arun, Jacobs, Michael, Srinivasan, Raghavan, O'Donncha, Fearghal
Climate change, population growth, and water scarcity present unprecedented challenges for agriculture. This project aims to forecast soil moisture using domain knowledge and machine learning for crop management decisions that enable sustainable farm
Externí odkaz:
http://arxiv.org/abs/2212.06565
Autor:
Andreea A. Creanga, Briana Kramer, Carrie Wolfson, Meighan Mary, Elizabeth M. Stierman, Sarah Clifford, Ada Ezennia, Jane Rhule, Nina Martin, Maxine Vance-Reed, Teneele Bruce, Bonnie DiPietro, Adriane Burgess, Nicole Warren, Shari N. Lawson, Sarah Meyerholz, Kelly Bower
Publikováno v:
Health Equity, Vol 8, Iss 1, Pp 406-418 (2024)
Objective: To describe two main pillars of the Maryland Maternal Health Innovation Program (MDMOM): (1) centering equity and (2) fostering broad stakeholder collaboration and trust. Methods: We summarized MDMOM?s key activities and used severe matern
Externí odkaz:
https://doaj.org/article/51167d54f2384078a7e6c8654a4882b8
Autor:
Loretta DiPietro, Jeffrey Bingenheimer, Sameera A. Talegawkar, Erica Sedlander, Hagere Yilma, Pratima Pradhan, Rajiv N. Rimal
Publikováno v:
Women's Health Reports, Vol 5, Iss 1, Pp 522-529 (2024)
Background: Anemia is associated with fatigue, low physical activity, and poor quality of life. The purpose of this study was to determine the effects of a field trial on 6-month change in anemia and physical activity among nonpregnant women living i
Externí odkaz:
https://doaj.org/article/ab3a59bf4689482797308db28eefc950
Autor:
DiPietro, Daniel M., Hazari, Vivek
Data is a key component of modern machine learning, but statistics for assessing data label quality remain sparse in literature. Here, we introduce DiPietro-Hazari Kappa, a novel statistical metric for assessing the quality of suggested dataset label
Externí odkaz:
http://arxiv.org/abs/2209.08243
Suicide is a major public health crisis. With more than 20,000,000 suicide attempts each year, the early detection of suicidal intent has the potential to save hundreds of thousands of lives. Traditional mental health screening methods are time-consu
Externí odkaz:
http://arxiv.org/abs/2209.05707
Autor:
DiPietro, Daniel M., Zhu, Bo
Here we present Symplectically Integrated Symbolic Regression (SISR), a novel technique for learning physical governing equations from data. SISR employs a deep symbolic regression approach, using a multi-layer LSTM-RNN with mutation to probabilistic
Externí odkaz:
http://arxiv.org/abs/2209.01521
Autor:
DiPietro, Daniel M.
Stopwords carry little semantic information and are often removed from text data to reduce dataset size and improve machine learning model performance. Consequently, researchers have sought to develop techniques for generating effective stopword sets
Externí odkaz:
http://arxiv.org/abs/2209.01519