Zobrazeno 1 - 10
of 1 424
pro vyhledávání: '"Risk modeling"'
Autor:
Ayat Al Assi, Rubayet Bin Mostafiz, Fatemeh Orooji, Arash Taghinezhad, Melanie Gall, Robert V. Rohli, Christopher T. Emrich, Carol J. Friedland, Eric Johnson
Publikováno v:
Resilient Cities and Structures, Vol 3, Iss 4, Pp 21-33 (2024)
Communicating risks and mitigation benefits associated with natural hazards such as wind to the general public is challenging given the location-dependency of parameters and the complexity of the problem. Web tools play a crucial role in educating re
Externí odkaz:
https://doaj.org/article/2ec680e09f8c43158dab59caa68e9d0f
Publikováno v:
Discover Oncology, Vol 15, Iss 1, Pp 1-20 (2024)
Abstract Background T-cell-related genes play a crucial role in LIHC development. However, a reliable prognostic profile based on risk models of these genes has yet to be identified. Methods Single-cell datasets from both tumor and normal tissue samp
Externí odkaz:
https://doaj.org/article/d96da8a3be174b68be493ec56ad8b598
Autor:
Martin Eiermann
Publikováno v:
Sociological Science, Vol 11, Iss 26, Pp 707-742 (2024)
Predictive Risk Modeling (PRM) tools are widely used by governing institutions, yet research on their effects has yielded divergent findings with low external validity. This study examines how such tools influence child welfare governance, using a qu
Externí odkaz:
https://doaj.org/article/948b12aa55944649bdfef0923bf25b98
Autor:
Deesha A Patel, Zachary A Marcum, Aisara Chansakul, Astra Toyip, Katherine Nerney, Catherine A Panozzo, Samantha St Laurent, Darshan Mehta, Parinaz Ghaswalla
Publikováno v:
Human Vaccines & Immunotherapeutics, Vol 20, Iss 1 (2024)
Morbidity and mortality caused by respiratory syncytial virus (RSV) in older adults and those with underlying health conditions can be potentially alleviated through vaccination. To assist vaccine policy decision-makers and payers, we estimated the a
Externí odkaz:
https://doaj.org/article/70e00bea3c4f4041b8432157361f1207
Publikováno v:
International Journal of Disaster Risk Science, Vol 15, Iss 3, Pp 421-433 (2024)
Abstract In this study, a broad range of supervised machine learning and parametric statistical, geospatial, and non-geospatial models were applied to model both aggregated observed impact estimate data and satellite image-derived geolocated building
Externí odkaz:
https://doaj.org/article/b913ac9b13b44f5f89ca9bd92c45963a
Publikováno v:
Rheumato, Vol 4, Iss 2, Pp 88-119 (2024)
Lyme disease is a zoonotic infectious disease. Increased public interest in Lyme disease has caused increased efforts by researchers for its surveillance and control. The main concept for this paper is to determine the mammalian species composition o
Externí odkaz:
https://doaj.org/article/f949828139494e2ca9edeaaa1b181b39
Publikováno v:
Journal of Accounting and Investment, Vol 25, Iss 1, Pp 152-171 (2024)
Research aims: Risk management in financial institutions struggles with setting suitable capital charges for operational losses, resulting in large, disproportionate reserves that impact profits. This study, therefore, aims to develop a tailored oper
Externí odkaz:
https://doaj.org/article/098e97ca3dd44f058009d7714d2e2031
Publikováno v:
IEEE Access, Vol 12, Pp 50673-50688 (2024)
Digital trends like blockchain have led to cryptocurrency payments becoming popular in e-commerce. While cryptocurrencies have benefited users, they have also attracted criminals who use them to commit cyberattacks and harm security. In this research
Externí odkaz:
https://doaj.org/article/bb47f9f900934e3cad8596a6a23310fb
Autor:
John P. Mickley, MD, Elizabeth S. Kaji, BA, Bardia Khosravi, MD, MPH, MHPE, Kellen L. Mulford, PhD, Michael J. Taunton, MD, Cody C. Wyles, MD
Publikováno v:
Arthroplasty Today, Vol 27, Iss , Pp 101396- (2024)
Hip and knee arthroplasty are high-volume procedures undergoing rapid growth. The large volume of procedures generates a vast amount of data available for next-generation analytics. Techniques in the field of artificial intelligence (AI) can assist i
Externí odkaz:
https://doaj.org/article/ee502c59cebc473d9a3421a8afe4ca3d