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• W2273922801 abstract "In today’s current practices, detecting melanoma in its early stages is a challengingtask for dermatologists. Early stage melanoma is nearly identical tobenign melanocytic lesions, requiring doctors to detect subtle changes in shapeor size of lesions that are easily missed, but are indicators of development ofthe disease. Dermatoscopy, a discipline that involves analyzing suspicious patternsin magnified pictures of skin lesions, helps dermatologists keep track ofthese changes. However, this approach has its shortcomings. Typically, the processof identifying melanoma is not consistent between doctors, or even withineach doctor. This results in two problems: (1) it creates data that is not comparablebetween doctors, such as when one doctor captures photos while anotherdoes not, and (2) it produces data that is not consistent within a doctor’s ownrecords of a patient from visit to visit, such as when they switch between capturingphotos of a mole or simply taking notes. In the second case, doctorsmay have gaps in photos available, causing difficulties in tracking the progressof moles. Further, their existing methods are time intensive, putting pressureon them to complete their evaluation quickly, and require them to perform actionsthat could be done by someone without a medical degree, such as takingpictures of a person’s moles.In our work, we introduce MoleMapper, an Android-based application thataddresses the issues above by enforcing a consistent workflow. The key insightin our work is that, by having a standardized, repeatable workflow, wecan create tooled support that both introduces consistency, and also automatesparts of the process that were previously tedious. MoleMapper does this by:(1) introducing a structured workflow which guides the user in taking fullbody pictures for the doctor to review, (2) making use of a subdivision of thebody that thoroughly captures all potential areas that may contain moles, and (3) automatically creating a mapping between the pictures taken by a dermatoscopeand the subdivisions introduced in the workflow. As opposed to existingtools that require dermatologists to context switch between a PC and camera,MoleMapper consolidates the entire process into a single device.We evaluated MoleMapper by performing both a semi-structured laboratoryexperiment, as well as an in-the-field study. In the first study, we collected feedbackfrom dermatologists during mock evaluations. In the second study, weinterviewed and collected feedback from dermatologists that used MoleMapperwith their own patients. Results indicate that dermatologists do indeedfind MoleMapper useful in their existing process. However, dermatologistsprefer to selectively choose which subdivisions need photographs, limiting theeffectiveness of the streamlined workflow. They find the interface intuitive, andthey see the single device approach as a significant improvement over their existingpractice of frequently switching between PC and camera.In future work, we aim to further integrate MoleMapper with its parentproject Cutis in Silico. MoleMapper is part of a family of tools that aim to fullyautomate the capture of full-body pictures, and provide doctors assistance indetecting Melanoma. One of our main goals will be to provide seamless datasynchronization between MoleMapper and PersonalScreener, a tool that letspatients monitor their own suspect lesions by taking dermatoscopic pictureswith their smartphones.The contributions of this dissertation are five-fold: (1) a summary of the differentworkflows practiced by dermatologists that was revealed in interviewswith 7 dermatologists. (2) A standard subdivision of the human body that canbe used when taking full-scale pictures of a patient. (3) A consolidated proposedworkflow for dermatologists that would bring thoroughness and consistencyto their practice. (4) An Android application to perform the proposedworkflow. (5) An evaluation in the form of a case study for the application andworkflow being used by dermatologists in-the-field." @default.
• W2273922801 created "2016-06-24" @default.
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• W2273922801 date "2015-01-01" @default.
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• W2273922801 title "A workflow for melanocytic lesion evaluation" @default.
• W2273922801 hasPublicationYear "2015" @default.
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