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Incorporating area-level social drivers of health in predictive algorithms using electronic health record data.
J Am Med Inform Assoc
January 2025
Department of Health Policy, Stanford School of Medicine, Stanford, CA 94305, United States.
Objectives: The inclusion of social drivers of health (SDOH) into predictive algorithms of health outcomes has potential for improving algorithm interpretation, performance, generalizability, and transportability. However, there are limitations in the availability, understanding, and quality of SDOH variables, as well as a lack of guidance on how to incorporate them into algorithms when appropriate to do so. As such, few published algorithms include SDOH, and there is substantial methodological variability among those that do.
View Article and Find Full Text PDFA deep learning tissue classifier based on differential Co-expression genes predicts the pregnancy outcomes of cattle.
Biol Reprod
January 2025
Inner Mongolia SK·Xing Animal Breeding and Breeding Biotechnology Research Institute Co., Ltd, Hohhot 011517, China.
Economic losses in cattle farms are frequently associated with failed pregnancies. Some studies found that the transcriptomic profiles of blood and endometrial tissues in cattle with varying pregnancy outcomes display discrepancies even before artificial insemination (AI) or embryo transfer (ET). In the study, 330 samples from seven distinct sources and two tissue types were integrated and divided into two groups based on the ability to establish and maintain pregnancy after AI or ET: P (pregnant) and NP (nonpregnant).
View Article and Find Full Text PDFHealth Care Professionals and Data Scientists' Perspectives on a Machine Learning System to Anticipate and Manage the Risk of Decompensation From Patients With Heart Failure: Qualitative Interview Study.
J Med Internet Res
January 2025
NOVA National School of Public Health, Public Health Research Centre, Comprehensive Health Research Center, NOVA University Lisbon, Lisbon, Portugal.
Background: Heart failure (HF) is a significant global health problem, affecting approximately 64.34 million people worldwide. The worsening of HF, also known as HF decompensation, is a major factor behind hospitalizations, contributing to substantial health care costs related to this condition.
View Article and Find Full Text PDFEstimating Trends in Cardiovascular Disease Risk for the EXPOSE (Explaining Population Trends in Cardiovascular Risk: A Comparative Analysis of Health Transitions in South Africa and England) Study: Repeated Cross-Sectional Study.
JMIR Cardio
January 2025
Faculty of Education, Health and Human Sciences, University of Greenwich, London, United Kingdom.
Background: Cardiovascular diseases (CVDs) are the leading cause of death globally. Demographic, behavioral, socioeconomic, health care, and psychosocial variables considered risk factors for CVD are routinely measured in population health surveys, providing opportunities to examine health transitions. Studying the drivers of health transitions in countries where multiple burdens of disease persist (eg, South Africa), compared with countries regarded as models of "epidemiologic transition" (eg, England), can provide knowledge on where best to intervene and direct resources to reduce the disease burden.
View Article and Find Full Text PDFPredictors of the Short-Term Outcomes of Guillain-Barré Syndrome: Exploring Electrodiagnostic and Clinical Features.
Brain Behav
January 2025
Department of Neurology, Chang Gung Memorial Hospital, Keelung, Taiwan.
Background And Objectives: Guillain-Barré syndrome (GBS), an acute inflammatory disorder of the peripheral nervous system, is characterized by muscle weakness and paralysis. Prompt identification of patients at a high risk of poor outcomes is crucial for timely intervention. In this study, we combined clinical data with nerve conduction study and electromyography data to identify the predictors of GBS outcomes.
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