Sustainable intensification (SI) is a multifaceted concept incorporating the ambition to increase or maintain the current level of agricultural yields while reduce negative ecological and environmental impacts. Decision-support systems (DSS) that use integrated analytical methods are often used to support decision making processes in agriculture. However, DSS often consist of set of values, objectives, and assumptions that may be inconsistent or in conflict with merits and objectives of SI. These potential conflicts will have consequences for adoption and up-take of agricultural research, technologies and related policies and regulations such as genetic technology in pursuit of SI. This perspective paper aimed at comparing a number of frequently used socio-economic DSS with respect to their capacity in incorporating various dimensions of SI, and discussing their application to analyzing farm animal genetic resources (FAnGR) policies. The case of FAnGR policies was chosen because of its great potential in delivering merits of SI. It was concluded that flexible DSS, with great integration capacity with various natural and social sciences, are needed to provide guidance on feasibility, practicality, and policy implementation for SI.
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http://dx.doi.org/10.3389/fgene.2015.00023 | DOI Listing |
Front Health Serv
December 2024
School of Social Work, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Background: Professionals who provide implementation support in human service systems describe relationships as being critical to support evidence use; however, developing trusting relationships are not strongly featured in implementation science literature. The aims of this study were to (a) assess the feasibility and acceptability of a theory-driven training and coaching approach for building trusting relationships among members of an implementation team who were supporting the implementation of an evidence-informed program in a public child welfare system in the United States and (b) gauge the initial efficacy of the approach in terms of the development of trusting relationships and subsequent implementation outcomes.
Methods: Consistent with a convergent mixed-methods approach, we collected both quantitative and qualitative data to address our research questions.
Radiother Oncol
December 2024
Department of Radiation Oncology, University Medical Center Leipzig, Leipzig, Germany; Comprehensive Cancer Center Central Germany, Partner Site Leipzig, Leipzig, Germany.
Purpose: Cumulative cisplatin doses of ≥ 200 mg/m improve survival in adults with head-and-neck squamous cell carcinoma (HNSCC) undergoing chemoradiation, but many older adults with HNSCC cannot receive this prognostically relevant dose due to toxicities. This study aims to develop predictive models to assess the likelihood of older adults with HNSCC receiving ≥ 200 mg/m cisplatin during chemoradiation.
Methods: 366 patients from the SENIOR database, an international cohort of adults ≥ 65 years with HNSCC, received definitive chemoradiation with single-agent cisplatin and were analyzed.
Background: This study addresses the intricate landscape of racial disparities in healthcare delivery, with a specific focus on surgical procedures. The concern was accentuated by the challenges posed during the COVID-19 pandemic when resources became scarce. Recognizing the potential impact of provider bias in medical decision-making, the American College of Surgeons introduced the Medically Necessary and Time-Sensitive (MeNTS) scoring system.
View Article and Find Full Text PDFChin Med J (Engl)
December 2024
State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results.
View Article and Find Full Text PDFComput Biol Med
December 2024
Department of Electrical and Electronic Engineering, Gazi University, Ankara, Turkey.
As one of the most common neurodegenerative diseases, Multiple sclerosis (MS) is a chronic immune-driven disorder that affects the central nervous system (CNS). Due to the variety of symptoms, accurately diagnosing MS demands rigorous attention to differential diagnosis, as various disorders can closely mimic its clinical and paraclinical features. Although MR imaging techniques are gold standards in diagnosing MS, the feasibility of advanced Electroencephalogram (EEG) signal processing methods is discussed in this study to detect patients with MS disorder.
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