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Health 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 PDFRetrospective analysis of disease characteristics and treatment patterns among patients with esophageal cancer across 14 surgically represented centers.
Cancer Biol Med
January 2025
State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Beijing Key Laboratory of Carcinogenesis and Translational Research, Department of Gastrointestinal Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Objective: Esophageal cancer (EC) ranks eighth among cancers in cancer-related deaths globally, and ~44% of new cases occur in China. We sought to describe the clinical characteristics and treatment landscape of EC in China before the approval of immunotherapy in 2020.
Methods: CHANNEL was a large, retrospective study using patient-level data from 14 hospitals/cancer centers across China, including adults initiating therapy for newly diagnosed EC (January to December 2018).
Large-scale commercial-grade volatile fatty acids production from sewage sludge and food waste: A holistic environmental assessment.
Environ Sci Ecotechnol
January 2025
CRETUS, Department of Chemical Engineering. Universidade de Santiago de Compostela, 15782, Santiago de Compostela, Spain.
The valorization of sewage sludge and food waste to produce energy and fertilizers is a well-stablished strategy within the circular economy. Despite the success of numerous laboratory-scale experiments in converting waste into high-value products such as volatile fatty acids (VFAs), large-scale implementation remains limited due to various technical and environmental challenges. Here, we evaluate the environmental performance of a hypothetical large-scale VFAs biorefinery located in Galicia, Spain, which integrates fermentation and purification processes to obtain commercial-grade VFAs based on primary data from pilot plant operations.
View Article and Find Full Text PDFRandomized Clinical Trial to Increase Self-Monitoring of Physical Activity and Eating Behaviors in Youth: A Feasibility Study.
Transl J Am Coll Sports Med
July 2024
Department of Implementation Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC.
Introduction: Mobile health (mHealth) has the potential to reduce reliance on in-person healthcare visits, making monitoring of health, eating, and physical activity less burdensome. There is a great need to develop and test mHealth tools for pediatric weight loss programs to enhance clinical practice. This study aimed to test the feasibility of utilizing a tailored suite of mHealth components to augment an existing evidence-based in-person pediatric weight management program.
View Article and Find Full Text PDFCurrent Practices and Perspectives of Artificial Intelligence in the Clinical Management of Eating Disorders: Insights From Clinicians and Community Participants.
Int J Eat Disord
January 2025
SEED Lifespan Strategic Research Centre, School of Psychology, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
Objective: Artificial intelligence (AI) could revolutionize the delivery of mental health care, helping to streamline clinician workflows and assist with diagnostic and treatment decisions. Yet, before AI can be integrated into practice, it is necessary to understand perspectives of these tools to inform facilitators and barriers to their uptake. We gathered data on clinician and community participant perspectives of incorporating AI in the clinical management of eating disorders.
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