Professional expectations and patient expectations concerning the development of Artificial Intelligence (AI) for the early diagnosis of Pulmonary Hypertension (PH)

The expectations of professionals working on the development of healthcare Artificial Intelligence (AI) technologies and the patients who will be affected by them have received limited attention. This paper reports on a Foresight Workshop with professionals involved with pulmonary hypertension (PH) and a Focus Group with members of a PH patient group, to discuss expectations of AI development and implementation. We show that while professionals and patients had similar expectations of AI, with respect to the priority of early diagnosis; data risks of privacy and reuse; and responsibility, other expectations differed. One important point of difference was in the attitude toward using AI to point up other potential health problems (in addition to PH). A second difference was in the expectations regarding how much clinical professionals should know about the role of AI in diagnosis. These findings allow us to better prepare for the future by providing a frank appraisal of the complexities of AI development with foresight, and the anxieties of key stakeholders

Are digital picturings representations?

The philosopher of art Roger Scruton has claimed that photographic images are not representations, on the basis of the role of causal rather than intentional processes in arriving at the content of a photographic image (Scruton, 1981). His claim was controversial at the time, and still is, but had the merit of being a springboard for asking important questions about what kinds of representation result from the technologies used in depicting and visualising. In the context of computational picturing of different kinds, in imaging and other forms of visualisation, the question arises again, but this time in an even more interesting form, since these techniques are often hybrids of different principles and techniques. A digital image results from a complex interrelationship of physical, mathematical and technological principles, embedded within human and social situations. This paper consists of three sections, each presenting a view of the question whether digital imaging and digital visual artefacts generally are representations, from a different perspective. These perspectives are not representative, but aim only to accomplish what Scruton’s paper did succeed in accomplishing, that is, being a provocation and a springboard for a broader discussion

Bridging Across Methods in the Biosciences

Cross-disciplinary research is essential if science is to properly address societal needs. In spite of several policy initiatives to foster such research across sectors, there is still a high level of compartmentalisation in the biosciences. The European Commission is preparing for a Missions based science and innovation strategy in which it will be important to consider how the goal of meaningful cross-disciplinarity can be achieved. This report aims to raise the question of cross-disciplinarity again, and to suggest specific actions to further the understanding, achievement and evaluation of cross-disciplinarity in the biosciences.JRC.F.3-Chemicals Safety and Alternative Method

Merleau-Ponty and the Measuring Body

In recent years a growing number of scholars in science studies and related fields are developing new ontologies to displace entrenched dualisms. These efforts often go together with a renewed interest in the roles played by symbolisms and tools in knowledge and being. This article brings Maurice Merleau-Ponty into these conversations, positioning him as a precursor of today’s innovative recastings of technoscience. While Merleau-Ponty is often invoked in relation to his early work on the body and embodiment, this article focuses on his later work, where the investigation of perception is integrated with an ontological exploration. The resulting approach revolves around the highly original idea of the body as a standard of measurement. We further develop this idea by coining the term ‘the measuring body’, which to a greater extent than did Merleau-Ponty accentuates the relative autonomy of symbolisms and tools and their capacity to decentre the perceiving body

Implicit trust in clinical decision-making by multidisciplinary teams

In clinical practice, decision-making is not performed by individual knowers but by an assemblage of people and instruments in which no one member has full access to every piece of evidence. This is due to decision making teams consisting of members with different kinds of expertise, as well as to organisational and time constraints. This raises important questions for the epistemology of medicine, which is inherently social in this kind of setting, and implies epistemic dependence on others. Trust in these contexts is a highly complex social practice, involving different forms of relationships between trust and reasons for trust: based on reasons, and not based on reasons; based on reasons that are easily accessible to reflection and others that are not. In this paper, we focus on what it means to have reasons to trust colleagues in an established clinical team, collectively supporting or carrying out every day clinical decision-making. We show two important points about these reasons, firstly, they are not sought or given in advance of a situation of epistemic dependence, but are established within these situations; secondly they are implicit in the sense of being contained or nested within other actions that are not directly about trusting another person. The processes of establishing these reasons are directly about accomplishing a task, and indirectly about trusting someone else’s expertise or competence. These processes establish a space of reasons within which what it means to have reasons for trust, or not, gains a meaning and traction in these team-work settings. Based on a qualitative study of decision-making in image assisted diagnosis and treatment of a complex disease called pulmonary hypertension (PH), we show how an intersubjective framework, or ‘space of reasons’ is established through team members forging together a common way of identifying and dealing with evidence. In dealing with images as a central diagnostic tool, this also involves a common way of looking at the images, a common mode or style of perception. These frameworks are developed through many iterations of adjusting and calibrating interpretations in relation to those of others, establishing what counts as evidence, and ranking different kinds of evidence. Implicit trust is at work throughout this process. Trusting the expertise of others in clinical decision-making teams occurs while the members of the team are busy on other tasks, most importantly, building up a framework of common modes of seeing, and common ways of identifying and assessing evidence emerge. It is only in this way that trusting or mistrusting becomes meaningful in these contexts, and that a framework for epistemic dependence is established

Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop

Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting

Implicit trust in clinical decision-making by multidisciplinary teams

In clinical practice, decision-making is not performed by individual knowers but by an assemblage of people and instruments in which no one member has full access to every piece of evidence. This is due to decision making teams consisting of members with different kinds of expertise, as well as to organisational and time constraints. This raises important questions for the epistemology of medicine, which is inherently social in this kind of setting, and implies epistemic dependence on others. Trust in these contexts is a highly complex social practice, involving different forms of relationships between trust and reasons for trust: based on reasons, and not based on reasons; based on reasons that are easily accessible to reflection and others that are not. In this paper, we focus on what it means to have reasons to trust colleagues in an established clinical team, collectively supporting or carrying out every day clinical decision-making. We show two important points about these reasons, firstly, they are not sought or given in advance of a situation of epistemic dependence, but are established within these situations; secondly they are implicit in the sense of being contained or nested within other actions that are not directly about trusting another person. The processes of establishing these reasons are directly about accomplishing a task, and indirectly about trusting someone else’s expertise or competence. These processes establish a space of reasons within which what it means to have reasons for trust, or not, gains a meaning and traction in these team-work settings. Based on a qualitative study of decision-making in image assisted diagnosis and treatment of a complex disease called pulmonary hypertension (PH), we show how an intersubjective framework, or ‘space of reasons’ is established through team members forging together a common way of identifying and dealing with evidence. In dealing with images as a central diagnostic tool, this also involves a common way of looking at the images, a common mode or style of perception. These frameworks are developed through many iterations of adjusting and calibrating interpretations in relation to those of others, establishing what counts as evidence, and ranking different kinds of evidence. Implicit trust is at work throughout this process. Trusting the expertise of others in clinical decision-making teams occurs while the members of the team are busy on other tasks, most importantly, building up a framework of common modes of seeing, and common ways of identifying and assessing evidence emerge. It is only in this way that trusting or mistrusting becomes meaningful in these contexts, and that a framework for epistemic dependence is established