Biomedical Research and Clinical Practice

10.15761/brcp ◽  
2020 ◽  
2020 ◽  
Author(s):  
Oliver Maassen ◽  
Sebastian Fritsch ◽  
Julia Gantner ◽  
Saskia Deffge ◽  
Julian Kunze ◽  
...  

BACKGROUND The increasing development of artificial intelligence (AI) systems in medicine driven by researchers and entrepreneurs goes along with enormous expectations for medical care advancement. AI might change the clinical practice of physicians from almost all medical disciplines and in most areas of healthcare. While expectations for AI in medicine are high, practical implementations of AI for clinical practice are still scarce in Germany. Moreover, physicians’ requirements and expectations of AI in medicine and their opinion on the usage of anonymized patient data for clinical and biomedical research has not been investigated widely in German university hospitals. OBJECTIVE Evaluate physicians’ requirements and expectations of AI in medicine and their opinion on the secondary usage of patient data for (bio)medical research e.g. for the development of machine learning (ML) algorithms in university hospitals in Germany. METHODS A web-based survey was conducted addressing physicians of all medical disciplines in 8 German university hospitals. Answers were given on Likert scales and general demographic responses. Physicians were asked to participate locally via email in the respective hospitals. RESULTS 121 (39.9%) female and 173 (57.1%) male physicians (N=303) from a wide range of medical disciplines and work experience levels completed the online survey. The majority of respondents either had a positive (130/303, 42.9%) or a very positive attitude (82/303, 27.1%) towards AI in medicine. A vast majority of physicians expected the future of medicine to be a mix of human and artificial intelligence (273/303, 90.1%) but also requested a scientific evaluation before the routine implementation of AI-based systems (276/303, 91.1%). Physicians were most optimistic that AI applications would identify drug interactions (280/303, 92.4%) to improve patient care substantially but were quite reserved regarding AI-supported diagnosis of psychiatric diseases (62/303, 20.5%). 82.5% of respondents (250/303) agreed that there should be open access to anonymized patient databases for medical and biomedical research. CONCLUSIONS Physicians in stationary patient care in German university hospitals show a generally positive attitude towards using most AI applications in medicine. Along with this optimism, there come several expectations and hopes that AI will assist physicians in clinical decision making. Especially in fields of medicine where huge amounts of data are processed (e.g., imaging procedures in radiology and pathology) or data is collected continuously (e.g. cardiology and intensive care medicine), physicians’ expectations to substantially improve future patient care are high. However, for the practical usage of AI in healthcare regulatory and organizational challenges still have to be mastered.


2003 ◽  
Vol 348 (12) ◽  
pp. 1170-1175 ◽  
Author(s):  
Esteban González Burchard ◽  
Elad Ziv ◽  
Natasha Coyle ◽  
Scarlett Lin Gomez ◽  
Hua Tang ◽  
...  

Pathogens ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 299 ◽  
Author(s):  
Vladimir V. Bamm ◽  
Jordan T. Ko ◽  
Iain L. Mainprize ◽  
Victoria P. Sanderson ◽  
Melanie K. B. Wills

Lyme disease is a complex tick-borne zoonosis that poses an escalating public health threat in several parts of the world, despite sophisticated healthcare infrastructure and decades of effort to address the problem. Concepts like the true burden of the illness, from incidence rates to longstanding consequences of infection, and optimal case management, also remain shrouded in controversy. At the heart of this multidisciplinary issue are the causative spirochetal pathogens belonging to the Borrelia Lyme complex. Their unusual physiology and versatile lifestyle have challenged microbiologists, and may also hold the key to unlocking mysteries of the disease. The goal of this review is therefore to integrate established and emerging concepts of Borrelia biology and pathogenesis, and position them in the broader context of biomedical research and clinical practice. We begin by considering the conventions around diagnosing and characterizing Lyme disease that have served as a conceptual framework for the discipline. We then explore virulence from the perspective of both host (genetic and environmental predispositions) and pathogen (serotypes, dissemination, and immune modulation), as well as considering antimicrobial strategies (lab methodology, resistance, persistence, and clinical application), and borrelial adaptations of hypothesized medical significance (phenotypic plasticity or pleomorphy).


2016 ◽  
Vol 1 (1) ◽  
pp. 66 ◽  
Author(s):  
Robert L Holland

The last decade has seen an extraordinary amount of effort devoted in biomedical research to the field of biomarkers. There have been some notable successes with novel markers being adopted into clinical practice bringing clear clinical benefit to some patients — particularly with the increasing numbers of medicines being approved with companion diagnostics. However, it is fair to say that there has not yet been the numbers of clinically valuable biomarkers brought to medical practice that the research effort would seem to warrant. This paper evaluates examples of successful biomarkers, markers which might be considered partial successes and a few problematic examples and ar-gues that more effort spent in the validation phase of marker development, and less in the discovery phase might be a more efficient way to allocate research resources.


2021 ◽  
Author(s):  
KV Zorin ◽  
KG Gurevich

Not only quarantine measures should be the main strategy for preventing COVID-19, but also large-scale vaccination of the population. Therefore, there are many ethical questions associated with obtaining voluntary informed consent in biomedical research and clinical practice. An ethical review of vaccination against a new coronavirus infection can be carried out fully and adequately provided that the ethical aspects of voluntary informed consent are observed. Without this, it is impossible to control the quality, efficacy and safety of the vaccine, and, consequently, the vaccination of patients and its results.


Author(s):  
Reinhard Heil ◽  
Nils B. Heyen ◽  
Martina Baumann ◽  
Bärbel Hüsing ◽  
Daniel Bachlechner ◽  
...  

The increasing availability of extensive and complex data has made human genomics and its applications in (bio)medicine an at­ tractive domain for artificial intelligence (AI) in the form of advanced machine learning (ML) methods. These methods are linked not only to the hope of improving diagnosis and drug development. Rather, they may also advance key issues in biomedicine, e. g. understanding how individual differences in the human genome may cause specific traits or diseases. We analyze the increasing convergence of AI and genom­ics, the emergence of a corresponding innovation system, and how these associative AI methods relate to the need for causal knowledge in biomedical research and development (R&D) and in medical prac­tice. Finally, we look at the opportunities and challenges for clinical practice and the implications for governance issues arising from this convergence.


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