A Multimodal, Usable, and Flexible Clinical Decision-Support System for Breast Cancer Diagnosis and Reporting
(2023) SN Computer Science — Vol. 4, n° 1, p. 49 (2023)
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- Abstract
- To support radiologists in their decision-making regarding women breast cancer diagnosis based on mammographies, this paper addresses three challenges posed by a Clinical Decision Support System (CDSS) for breast cancer screening, diagnosis, and reporting: multimodality (via textual, graphical, and two-dimensional gestural interaction), usability (via human-computer interactions methods such as knowledge elicitation interviews, scenario-focused questionnaires, multi-fidelity prototyping and user testing), and flexibility (via selected image processing techniques ensuring manual and semi-automatic annotation of breast cancer findings based on radiologists' gestures)
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Citations
Kieffer, S., Vanderdonckt, J., & Gouze, A. (2023). A Multimodal, Usable, and Flexible Clinical Decision-Support System for Breast Cancer Diagnosis and Reporting. SN Computer Science, 4(1), 49. https://doi.org/10.1007/s42979-022-01451-z (Original work published 2023)