The development and evaluation of CADMIUM: a prototype system to assist in the interpretation of mammograms

Taylor, Paul; Fox, John; Pokropek, A. Todd

doi:10.1016/s1361-8415(99)80027-9

Cited by 27 publications

(9 citation statements)

References 28 publications

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“…A variety of decision support applications based on PROforma technology have demonstrated a significant positive impact on a number of outcome measures such as reducing prescription errors and adherence to evidence-based guidelines. [26][27][28] The DA captured patient demographic and clinical information (eg, histology type, evidence of extramural vascular invasion), as well as patient fitness to undergo chemotherapy (assessed via the presence of comorbidity and ECOG performance status 29 ranging from fit and well (0) to bed bound (4)).…”

Section: Development Of the Damentioning

confidence: 99%

Use of a computerised decision aid (DA) to inform the decision process on adjuvant chemotherapy in patients with stage II colorectal cancer: development and preliminary evaluation

et al. 2017

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ObjectivesTo develop a computerised decision aid (DA) to inform the decision process on adjuvant chemotherapy in patients with stage II colorectal cancer, and examine perceived usefulness, acceptability and areas for improvement of the DA.DesignMixed methods.SettingSingle outpatient oncology department in central London.ParticipantsConsecutive recruitment of 13 patients with stage II colorectal cancer, 12 of whom completed the study. Inclusion criteria were: age >18 years; complete resection for stage II adenocarcinoma of the colon or rectum; patients within 14–56 days after surgery; no contraindication to adjuvant chemotherapy; able to give written informed consent. Exclusion criterion: previous chemotherapy.Primary outcomesPatient perceived usefulness (assessed by the PrepDM questionnaire) and acceptability of the DA.ResultsPrepDM scores, measuring the perceived usefulness of the DA in preparing the patient to communicate with their doctor and make a health decision, were above those reported in other patient groups. Patient acceptability scores were also high; however, interviews showed that there was evidence of a lack of understanding of key information among some patients, in particular their baseline risk of recurrence, the net benefit of combination chemotherapy and the rationale for having chemotherapy when cancer had apparently gone.ConclusionsPatients found the DA acceptable and useful in supporting their decision about whether or not to have adjuvant chemotherapy. Suggested improvements for the DA include: sequential presentation of treatment options (eg, no treatment vs 1 drug, 1 drug vs 2 drugs) to enhance patient understanding of the difference between combination and single therapy, diagrams to help patients understand the rationale for chemotherapy to prevent a recurrence and inbuilt checks on patient understanding of baseline risk of recurrence and net benefit of chemotherapy.

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Section: Development Of the Damentioning

confidence: 99%

Use of a computerised decision aid (DA) to inform the decision process on adjuvant chemotherapy in patients with stage II colorectal cancer: development and preliminary evaluation

et al. 2017

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“…However, the resulting knowledge base was considered by radiologists to be confusing and in some respects erroneous [10]. One problem was that many statements were ambiguous if presented without other contextual information provided in the texts.…”

Section: Acquisition Of Radiological Knowledgementioning

confidence: 99%

“…The system uses symbolic reasoning to relate information obtained from image processing to the decisions that radiologists take. The system is an advanced version of CADMIUM, a prototype that was successfully evaluated with radiographers trained to interpret mammograms [10].…”

Section: Introductionmentioning

confidence: 99%

Elicitation and Representation of Expert Knowledge for Computer Aided Diagnosis in Mammography

Taylor¹,

Lee²,

Alberdi³

2004

Methods Inf Med

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This is the unspecified version of the paper.This version of the publication may differ from the final published version. We used these data to design a scheme with 50 descriptors. In Study 2, ten radiologists used the scheme to describe 40 sets of calcifications. We assessed the capacity of the terms to discriminate between benign and malignant calcifications, testing them against radiologists' assessments of malignancy and follow-up data. Permanent repository link Results:The descriptors that were found to be the most discriminating in Study 2 were included in CADIMUM II's knowledge base. They were represented as arguments for either a benign or a malignant diagnosis. These arguments are the central component of the decision support provided by the system. Other components are: image processing algorithms for the detection and measurement of calcifications and a set of rules that use the measures to decide which of the arguments apply to a given set of calcifications.. Conclusions:Preliminary evaluations of the CADMIUM II prototype reinforce the value of representing explicitly decision making processes in computer aided mammography and of deriving these processes from image processing measurements. Decision support is presented here at a level of description that is both relevant and meaningful to the user.

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“…In an evaluation of this decision procedure medical radiographers were asked to review a set of mammograms to find any abnormalities and make decisions about the diagnosis. CADMIUM demonstrated clear improvements in their ability to achieve this successfully [25]. Each of these three systems applies a body of medical knowledge to the decisionmaking process.…”

Section: Practical Argumentmentioning

confidence: 99%

Probability, logic and the cognitive foundations of rational belief

Fox

2003

Journal of Applied Logic

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Since Pascal introduced the idea of mathematical probability in the 17th century discussions of uncertainty and "rational" belief have been dogged by philosophical and technical disputes. Furthermore, the last quarter century has seen an explosion of new questions and ideas, stimulated by developments in the computer and cognitive sciences. Competing ideas about probability are often driven by different intuitions about the nature of belief that arise from the needs of different domains (e.g., economics, management theory, engineering, medicine, the life sciences etc). Taking medicine as our focus we develop three lines of argument (historical, practical and cognitive) that suggest that traditional views of probability cannot accommodate all the competing demands and diverse constraints that arise in complex real-world domains. A model of uncertain reasoning based on a form of logical argumentation appears to unify many diverse ideas. The model has precursors in informal discussions of argumentation due to Toulmin, and the notion of logical probability advocated by Keynes, but recent developments in artificial intelligence and cognitive science suggest ways of resolving epistemological and technical issues that they could not address. Crown

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The development and evaluation of CADMIUM: a prototype system to assist in the interpretation of mammograms

Cited by 27 publications

References 28 publications

Use of a computerised decision aid (DA) to inform the decision process on adjuvant chemotherapy in patients with stage II colorectal cancer: development and preliminary evaluation

Use of a computerised decision aid (DA) to inform the decision process on adjuvant chemotherapy in patients with stage II colorectal cancer: development and preliminary evaluation

Elicitation and Representation of Expert Knowledge for Computer Aided Diagnosis in Mammography

Probability, logic and the cognitive foundations of rational belief

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