This continuing education module reviews the uses of ways of knowing and ways of learning to assist the childbirth educator become a master teacher who facilitates the growth of the learner.
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http://dx.doi.org/10.1624/105812400X87725 | DOI Listing |
J Chem Inf Model
January 2025
Geneis (Beijing) Co. Ltd., Beijing 100102, China.
Identification of potential drug-target interactions (DTIs) is a crucial step in drug discovery and repurposing. Although deep learning effectively deciphers DTIs, most deep learning-based methods represent drug features from only a single perspective. Moreover, the fusion method of drug and protein features needs further refinement.
View Article and Find Full Text PDFJMIR Cancer
January 2025
Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands.
Background: The rising number of cancer survivors and the shortage of health care professionals challenge the accessibility of cancer care. Health technologies are necessary for sustaining optimal patient journeys. To understand individuals' daily lives during their patient journey, qualitative studies are crucial.
View Article and Find Full Text PDFContemp Nurse
January 2025
School of Nursing and Midwifery, Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Australia.
Background: In an undergraduate Bachelor of Nursing course, students enrol in an evidence-based Practice (EBP) subject. Three scaffolded tasks assess students' ability to find, summarise and synthesise professional literature. For each assessment task, students are provided feedback that informs subsequent assessments.
View Article and Find Full Text PDFPurpose: This brief report aims to summarize and discuss the methodologies of eXplainable Artificial Intelligence (XAI) and their potential applications in surgery.
Methods: We briefly introduce explainability methods, including global and individual explanatory features, methods for imaging data and time series, as well as similarity classification, and unraveled rules and laws.
Results: Given the increasing interest in artificial intelligence within the surgical field, we emphasize the critical importance of transparency and interpretability in the outputs of applied models.
Biomater Transl
November 2024
Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China.
The convergence of organoid technology and artificial intelligence (AI) is poised to revolutionise oral healthcare. Organoids - three-dimensional structures derived from human tissues - offer invaluable insights into the complex biology of diseases, allowing researchers to effectively study disease mechanisms and test therapeutic interventions in environments that closely mimic in vivo conditions. In this review, we first present the historical development of organoids and delve into the current types of oral organoids, focusing on their use in disease models, regeneration and microbiome intervention.
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