We may be at the cusp of a next generation framework for science which can be facilitated by understanding current limitations in the context of a divergence of 'scientific' tradition from the Axial Age (800-200 BCE) to the present. A powerful advance may come from fusing certain elements from Western and Eastern traditions, synthesizing the framework with an apt understanding of the divergence. Key traits will include the ethopoetic nature of the scientist with attention to his/her experience of self. The framework will also 'access' knowledge through a state of mind less encumbered with paradoxes, duality, incompatibility and other aporias. Case studies in biology and physics illustrate possibilities.
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http://dx.doi.org/10.1016/j.pbiomolbio.2017.08.016 | DOI Listing |
Biomed Phys Eng Express
January 2025
Applied Sciences, Indian Institute of Information Technology Allahabad, Deoghat, Jhalwa, Allahabad, 211012, INDIA.
Photoacoustic tomography (PAT) is a non-destructive, non-ionizing, and rapidly expanding hybrid biomedical imaging technique, yet it faces challenges in obtaining clear images due to limited data from detectors or angles. As a result, the methodology suffers from significant streak artifacts and low-quality images. The integration of deep learning (DL), specifically convolutional neural networks (CNNs), has recently demonstrated powerful performance in various fields of PAT.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition, Deakin University, Burwood, Australia.
Background: Heart failure (HF) is a chronic, progressive condition where the heart cannot pump enough blood to meet the body's needs. In addition to the daily challenges that HF poses, acute exacerbations can lead to costly hospitalizations and increased mortality. High health care costs and the burden of HF have led to the emerging application of new technologies to support people living with HF to stay well while living in the community.
View Article and Find Full Text PDFJMIR Cancer
January 2025
Wolfson Institute of Population Health, Queen Mary University of London, London, United Kingdom.
Background: Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial intelligence (AI) technologies have been applied to skin cancer diagnosis, but many technologies lack clinical evidence and/or the appropriate regulatory approvals.
View Article and Find Full Text PDFJ Particip Med
January 2025
Department of Ambulatory Care, Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Background: Health authorities worldwide have invested in digital technologies to establish robust information exchange systems for improving the safety and efficiency of medication management. Nevertheless, inaccurate medication lists and information gaps are common, particularly during care transitions, leading to avoidable harm, inefficiencies, and increased costs. Besides fragmented health care processes, the inconsistent incorporation of patient-driven changes contributes to these problems.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Prevention and Evaluation, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Background: Information exchange regarding the scope and content of health studies is becoming increasingly important. Digital methods, including study websites, can facilitate such an exchange.
Objective: This scoping review aimed to describe how digital information exchange occurs between the public and researchers in health studies.
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