Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal.
PLoS One
January 2025
Nova School of Business and Economics, Universidade Nova de Lisboa, Carcavelos, Portugal.
This empirical study assessed the potential of developing a machine-learning model to identify children and adolescents with poor oral health using only self-reported survey data. Such a model could enable scalable and cost-effective screening and targeted interventions, optimizing limited resources to improve oral health outcomes. To train and test the model, we used data from 2,133 students attending schools in a Portuguese municipality.
View Article and Find Full Text PDFAutomating alloy design and discovery with physics-aware multimodal multiagent AI.
Proc Natl Acad Sci U S A
January 2025
Laboratory for Atomistic and Molecular Mechanics, Massachusetts Institute of Technology, Cambridge, MA 02139.
The design of new alloys is a multiscale problem that requires a holistic approach that involves retrieving relevant knowledge, applying advanced computational methods, conducting experimental validations, and analyzing the results, a process that is typically slow and reserved for human experts. Machine learning can help accelerate this process, for instance, through the use of deep surrogate models that connect structural and chemical features to material properties, or vice versa. However, existing data-driven models often target specific material objectives, offering limited flexibility to integrate out-of-domain knowledge and cannot adapt to new, unforeseen challenges.
View Article and Find Full Text PDFClinical use of measurable residual disease in adult ALL: recommendations from a panel of U.S. experts.
Blood Adv
January 2025
University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States.
Measurable residual disease (MRD) is a powerful predictor of clinical outcomes in acute lymphoblastic leukemia (ALL). In addition to its clear prognostic importance, MRD information is increasingly used in clinical decision algorithms to guide therapeutic interventions. While it is well-established that achievement of MRD-negative remission is an important endpoint of ALL therapy, the prognostic and therapeutic implications of MRD in an individual patient are influenced by both disease-related factors (e.
View Article and Find Full Text PDFStrengthening National Immunization Technical Advisory Groups: Twelve Years of Progress (2012-2023).
Vaccines (Basel)
January 2025
World Health Organization (WHO), 1211 Geneva, Switzerland.
Introduction: Well-functioning National Immunization Technical Advisory Groups (NITAGs) are valuable contributors to decision-making processes in the complex immunization policy arena. This paper describes the progress made globally on the establishment and strengthening of these key advisory groups and discusses some of their strengths, challenges, and opportunities.
Methods: The data submitted annually by countries to the World Health Organization (WHO) via the WHO/UNICEF Joint Reporting Form (JRF) were analyzed, comparing the NITAG functionality criteria in 2012 and 2023.
Experience with a Self-Management Education Program for Adolescents with Type 1 Diabetes: A Qualitative Study.
Nurs Rep
January 2025
Nursing Research, Innovation and Development Centre of Lisbon (CIDNUR), University of Lisbon, Nursing School of Lisbon, 1600-190 Lisbon, Portugal.
: Adolescents with type 1 diabetes face complex challenges associated with the disease, underscoring the importance of developing self-management skills. This study examined participants' perspectives on a type 1 diabetes self-management education program. : Focus group interviews were conducted with 32 adolescents with type 1 diabetes who participated in the program and six expert patients.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!