Journal of evaluation in clinical practice
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This study is a case study that aims to evaluate community-based mental health services from the perspective of health providers and service recipients through SWOT analysis. ⋯ Community-based mental health services contain strengths, weaknesses, opportunities and threats according to the views of both health providers and service recipients, and the views of the groups overlap with each other within the supply-demand mechanism. It can be said that the effectiveness of community-based mental health services will increase by preventing threats by improving weaknesses and increasing the visibility of opportunities by recognizing strengths.
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The potential applications of large language models (LLMs)-a form of generative artificial intelligence (AI)-in medicine and health care are being increasingly explored by medical practitioners and health care researchers. ⋯ Accordingly, this paper finds a strong case for the incorporation of LLMs into clinical practice and, if their risk of patient harm is sufficiently mitigated, this incorporation might be ethically required, at least according to principlism.
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This article identifies and offers a response to several problems that affect the quality of both clinical education and health care services. These matters are: that in clinical training and practice, health, as lived by patients (persons), is not properly considered, and is equated reductively with treating diseases/disorders; that health is seen through disease, and as restricted to a single model defined by an organism's meeting (or being returned to) biochemical or functional standards; that intellectual assumptions instilled in schools of Medicine and Psychology about realities pertaining to healthcare determine an understanding of chronic illness or life with chronic challenges focused on impairment and suffering, and not on the fuller experience of living with illness, disability or neuropsychological challenges that patients have as persons; that arts-based education reflects the same focus in understanding 'illness', and thus neglects giving attention to the creation of personal health states of those living with challenging or debilitating long-term conditions; that, consequently, the arts are instrumentalized to serve these predefined educational purposes, rather than allowed to inform clinical training through that which is intrinsic or more specific to them. As a way out of these limitations and as an illustration of how things could be done differently, Vincent Van Gogh's paintings of the Sunflowers are used as visual inspiration for how we could change the way we see, and construct new mental representations of 'health', 'chronic illness' or 'chronic challenges', 'patient as person' or even 'person as non-patient', 'the clinician's role' and 'the identity of clinical practice'. Relying on Van Gogh's depictions of the sunflowers as an example and a visual basis, the article shows how characteristics typical to art (transformation, alternative generation, etc.) can be transferred into the perception and conceptualisation of clinically relevant realities, and discusses the benefits of these changes for clinical practice.
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3D Magnetic Resonance Imaging (3D-MRI) analysis of brain tumours is an important tool for gathering information needed for diagnosis and disease therapy planning. However, during the brain tumor segmentation process existing techniques have segmentation error while identifying tumor location and extended tumor regions due to improper extraction of initial contour points and overlapping tissue intensity distributions. ⋯ The results obtained for the BraTS2020 and Brain Tumor Detection 2020 data sets showed that the proposed model outperforms existing techniques with excellent precision of 97%, 97.5%, recall of 99%, 97.8%, and accuracy of 95.7%, 98.4%, respectively.
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This commentary on Sturmberg and Mercuri's paper 'Every Problem is Embedded in a Greater Whole' [1] argues that those authors have approached complexity from a largely mathematical perspective, drawing on the work of Sumpter. Whilst such an approach allows us to challenge the simple linear causality assumed in randomised controlled trials, it is itself limited. ⋯ It overlooks, for example, how science itself is historically and culturally shaped and how values-driven misunderstandings and conflicts are inevitable when people with different world views come together to try to solve a problem. This paper argues that the mathematical version of complexity thinking is necessary but not sufficient in medical research, and that we need to enhance such thinking further with attention to human values.