Publications by authors named "R Bloom"
Background And Objectives: We conducted a national survey to assess the opinions and experiences of transplant center staff related to processes of care graduation.
Methods: Following IRB approval, medical staff at U.S.
Factors Associated with Abnormal Mammogram Results Among Low-Income Uninsured Populations in Medically Underserved And Rural Texas Regions.
Womens Health Rep (New Rochelle)
September 2024
Article Synopsis
- - The study examined how neighborhood factors, rural settings, and ethnicity/race impact breast cancer screening in underserved areas of Central Texas, highlighting the effects of limited access to preventive care on screening rates.
- - Using data from breast and cervical cancer screening programs, researchers found that while residency characteristics didn't significantly influence abnormal mammogram results, individual factors did, notably showing that non-Hispanic white women had higher odds of abnormal outcomes compared to Hispanic women.
- - The findings suggest a link between educational levels in communities and abnormal mammography outcomes, indicating a need for further research on contextual risk factors and targeted interventions for better breast cancer prevention.
Medication education and adherence assessments are integral to kidney transplant success. This program evaluation aimed to describe candidate-reported findings using a standardized medication adherence assessment in candidates undergoing living-donor kidney transplantation. This was a single-center retrospective description of medication adherence on adult HIV-negative living-donor candidates from July 1, 2018 to December 1, 2018 who had ≥6 months post-operative follow-up.
View Article and Find Full Text PDFThe conventional computing paradigm struggles to fulfill the rapidly growing demands from emerging applications, especially those for machine intelligence because much of the power and energy is consumed by constant data transfers between logic and memory modules. A new paradigm, called "computational random-access memory (CRAM)," has emerged to address this fundamental limitation. CRAM performs logic operations directly using the memory cells themselves, without having the data ever leave the memory.
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