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Exploring Asian maternal experiences and mHealth needs for postpartum mental health care.
Digit Health
October 2024
Department of Psychiatry, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
Background: Mental health care during the postpartum period is notably underexplored within Asian demographics, with barriers such as stigma, privacy concerns, logistical challenges, and a shortage of mental health professionals that limits access to optimal mental healthcare. Previous studies found that mobile health (mHealth) technology has been offering a promising solution to these issues. However, the perspectives of mothers on existing mental health services and their mHealth needs are still not well understood and warrant further exploration.
View Article and Find Full Text PDF'Applications of machine learning in liposomal formulation and development'.
Pharm Dev Technol
January 2025
School of Medicine, University of Jordan, Amman, Jordan.
Machine learning (ML) has emerged as a transformative tool in drug delivery, particularly in the design and optimization of liposomal formulations. This review focuses on the intersection of ML and liposomal technology, highlighting how advanced algorithms are accelerating formulation processes, predicting key parameters, and enabling personalized therapies. ML-driven approaches are restructuring formulation development by optimizing liposome size, stability, and encapsulation efficiency while refining drug release profiles.
View Article and Find Full Text PDFDissecting the Molecular Structure of the Air/Ice Interface from Quantum Simulations of the Sum-Frequency Generation Spectrum.
J Am Chem Soc
January 2025
Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States.
Ice interfaces are pivotal in mediating key chemical and physical processes such as heterogeneous chemical reactions in the environment, ice nucleation, and cloud microphysics. At the ice surface, water molecules form a quasi-liquid layer (QLL) with properties distinct from those of the bulk. Despite numerous experimental and theoretical studies, a molecular-level understanding of the QLL has remained elusive.
View Article and Find Full Text PDFDual-Driven Activation of High-Valence States in Prussian Blue Analogues Via Graphene-Quantum Dots and Ozone-Induced Surface Restructuring for Superior Hydrogen Evolution Electrocatalyst.
Small Methods
January 2025
Department of Chemical Engineering, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan.
Electrochemical water splitting is a pivotal process for sustainable hydrogen energy production, relying on efficient hydrogen evolution reaction (HER) catalysts, particularly in acidic environments, where both high activity and durability are crucial. Despite the favorable kinetics of platinum (Pt)-based materials, their performance is hindered under harsh conditions, driving the search for alternatives. Due to their unique structural characteristic, Prussian blue analogs (PBAs) emerge as attractive candidates for designing efficient HER electrocatalysts.
View Article and Find Full Text PDFRepeatable process for extracting health data from HL7 CDA documents.
J Biomed Inform
January 2025
Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia; STACC, 51009 Tartu, Estonia.
Objective: This study aims to address the gap in the literature on converting real-world Clinical Document Architecture (CDA) data into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), focusing on the initial steps preceding the mapping phase. We highlight the importance of a repeatable Extract-Transform-Load (ETL) pipeline for health data extraction from HL7 CDA documents in Estonia for research purposes.
Methods: We developed a repeatable ETL pipeline to facilitate the extraction, cleaning, and restructuring of health data from CDA documents to OMOP CDM, ensuring a high-quality and structured data format.
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