A cooperative approach to decision support in the differential diagnosis of breast disease

Heathfield, Heather; Kirkham, N.

doi:10.3109/14639239209012133

Cited by 9 publications

(6 citation statements)

References 25 publications

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“…The "technology" theme was identified in data relating to digital pathology advances, including anatomical pathologists' The perceived applications and implications digital advances within anatomical pathology practice "…soon every histopathologist will expect to be able to exchange electronic images with colleagues" (Ref. [52] competition with technology may exist, 6,34,53,55,58,63,64 but the degree to which technology will wholly replace pathologists' role in AP practice remains debated.…”

Section: Technologymentioning

confidence: 99%

Responding to the healthcare workforce shortage: A scoping review exploring anatomical pathologists' professional identities over time

Rozario

Sarkar

Farlie

et al. 2023

Anatomical Sciences Ed

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Anatomical pathology (AP) is an anatomy‐centric medical specialty devoted to tissue‐based diagnosis of disease. The field faces a current and predicted workforce shortage, likely increasing diagnostic wait times and delaying patient access to urgent treatment. A lack of AP exposure is proposed to preclude recruitment to the field, as medical students are afforded only a limited understanding of who a pathologist is and what they do (their professional identity/PI and role). Anatomical sciences educators may be well placed to increase student understanding of anatomical pathologists' PI features, but until features of anatomical pathologists' PI are understood, recommendations for anatomy educators are premature. Thus, this scoping review asked: “What are the professional identity features of anatomical pathologists reported in the literature, and how have these changed over time?” A six‐stage scoping review was performed. Medline and PubMed, Global Health, and Embase were used to identify relevant studies (n = 74). Team‐based framework analysis identified that features of anatomical pathologists' professional identity encompass five overarching themes: professional practice, views about the role, training and education, personal implications, and technology. Technology was identified as an important theme of anatomical pathologists' PI, as it intersected with many other PI feature themes, including diagnosis and collaboration. This review found that pathologists may sometimes perceive professional competition with technology, such as artificial intelligence. These findings suggest unique opportunities for integrating AP‐specific PI features into anatomy teaching, which may foster student interest in AP, and potentially increase recruitment into the field.

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Section: Technologymentioning

confidence: 99%

Responding to the healthcare workforce shortage: A scoping review exploring anatomical pathologists' professional identities over time

Rozario

Sarkar

Farlie

et al. 2023

Anatomical Sciences Ed

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“…Breast cancer has been of interest since the days of ‘old AI’, applied to problems including differential diagnosis [ 7 ], grading [ 8 ], and prognosis and management [ 9 ]. Breast cancer is also an important use case in ‘new AI’, especially for screening and diagnosis [ 10 , 11 ].…”

Section: What Is Ai and How Is It Being Used In Breast Cancer Care?mentioning

confidence: 99%

The ethical, legal and social implications of using artificial intelligence systems in breast cancer care

et al. 2020

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Breast cancer care is a leading area for development of artificial intelligence (AI), with applications including screening and diagnosis, risk calculation, prognostication and clinical decision-support, management planning, and precision medicine. We review the ethical, legal and social implications of these developments. We consider the values encoded in algorithms, the need to evaluate outcomes, and issues of bias and transferability, data ownership, confidentiality and consent, and legal, moral and professional responsibility. We consider potential effects for patients, including on trust in healthcare, and provide some social science explanations for the apparent rush to implement AI solutions. We conclude by anticipating future directions for AI in breast cancer care. Stakeholders in healthcare AI should acknowledge that their enterprise is an ethical, legal and social challenge, not just a technical challenge. Taking these challenges seriously will require broad engagement, imposition of conditions on implementation, and pre-emptive systems of oversight to ensure that development does not run ahead of evaluation and deliberation. Once artificial intelligence becomes institutionalised, it may be difficult to reverse: a proactive role for government, regulators and professional groups will help ensure introduction in robust research contexts, and the development of a sound evidence base regarding real-world effectiveness. Detailed public discussion is required to consider what kind of AI is acceptable rather than simply accepting what is offered, thus optimising outcomes for health systems, professionals, society and those receiving care.

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“…In contrast computers have been shown to be inefficient at initial hypothesis restriction (which explains the interminably long datagathering sessions of some ES), but efficient at applying detailed differential criteria consistently to a small number of hypotheses (Blois, 1980). To capitalize upon the strengths of pathologists but augment their weaknesses, I designed a 'cooperative model of decision making' (Heathfield & Kirkham, 1992) and an inference mechanism based upon the theory of hypergraphs and social choice, which would optimize data gathering under conditions of uncertain and incomplete knowledge (Heathfield et al, 1991c).…”

Section: The 'Rise Of Es' and Ai In Medicine: The 1970smentioning

confidence: 99%

The rise and ‘fall’ of expert systems in medicine

Heathfield¹

1999

Expert Systems

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This paper represents a personal perspective on the last 13 years of research in medical artificial intelligence and expert systems, and describes the progress of the discipline from its inception to its current status. The challenges faced by researchers are examined, and it is argued that (despite the claims) theoretical and technical limitations are not the major barriers to the successful implementation of medical artificial intelligence and expert systems, but rather more complex professional and organizational issues are at stake.

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A cooperative approach to decision support in the differential diagnosis of breast disease

Cited by 9 publications

References 25 publications

Responding to the healthcare workforce shortage: A scoping review exploring anatomical pathologists' professional identities over time

Responding to the healthcare workforce shortage: A scoping review exploring anatomical pathologists' professional identities over time

The ethical, legal and social implications of using artificial intelligence systems in breast cancer care

The rise and ‘fall’ of expert systems in medicine

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