98%
921
2 minutes
20
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1056/NEJMsb2507600 | DOI Listing |
Background: Transforming Clinical Practice Guideline (CPG) recommendations into computer readable language is a complex and ongoing process that requires significant resources, including time, expertise, and funds. The objective is to provide an extension of the widely used GIN-McMaster Guideline Development Checklist (GDC) and Tool for the development of computable guidelines (CGs).
Methods: Based on an outcome from the Human Centered Design (HCD) workshop hosted by the Guidelines International Network North America (GIN-NA), a team was formed to develop the checklist extension.
Med Phys
September 2025
Department of Radiation Oncology, Mayo Clinic in Florida, Jacksonville, Florida, USA.
Background: Dose-driven continuous scanning (DDCS) enhances the efficiency and precision of proton pencil beam delivery by reducing beam pauses inherent in discrete spot scanning (DSS). However, current DDCS optimization studies using traveling salesman problem (TSP) formulations often rely on fixed beam intensity and computationally expensive interpolation for move spot generation, limiting efficiency and methodological robustness.
Purpose: This study introduces a Break Spot-Guided (BSG) method, combined with two acceleration strategies-dose rate skipping and bounding-to optimize beam intensity while minimizing beam delivery time (BDT).
JMIR Med Inform
September 2025
Global Health Economics Centre, Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Background: Artificial intelligence (AI) algorithms offer an effective solution to alleviate the burden of diabetic retinopathy (DR) screening in public health settings. However, there are challenges in translating diagnostic performance and its application when deployed in real-world conditions.
Objective: This study aimed to assess the technical feasibility of integration and diagnostic performance of validated DR screening (DRS) AI algorithms in real-world outpatient public health settings.
J Hazard Mater
September 2025
Department of Public Health Sciences, University of Texas at El Paso, 211 Kelly Hall, 500 W University, El Paso, TX 79902, USA. Electronic address:
The correlation between Pb species formation and bioaccessibility in alkaline, smelter-impacted soil co-contaminated with other toxic trace elements after treatment with phosphorus-containing amendments was investigated. The soil was collected near a former copper smelter, El Paso, Texas. It contained Pb (3200 ± 142 mg kg), As (254 ± 14 mg kg), and Cd (110 ± 8 mg kg).
View Article and Find Full Text PDFEmerg Top Life Sci
September 2025
Hurdle.bio / Chronomics Ltd., London, UK.
Artificial intelligence (AI) is transforming many fields, including healthcare and medicine. In biomarker discovery, AI algorithms have had a profound impact, thanks to their ability to derive insights from complex high-dimensional datasets and integrate multi-modal datatypes (such as omics, electronic health records, imaging or sensor and wearable data). However, despite the proliferation of AI-powered biomarkers, significant hurdles still remain in translating them to the clinic and driving adoption, including lack of population diversity, difficulties accessing harmonised data, costly and time-consuming clinical studies, evolving AI regulatory frameworks and absence of scalable diagnostic infrastructure.
View Article and Find Full Text PDF