Jonathan Kentley's research while affiliated with Chelsea and Westminster Hospital NHS Foundation Trust and other places
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Publications (5)
Background
Dermoscopy is commonly used for the evaluation of pigmented lesions, but agreement between experts for identification of dermoscopic structures is known to be relatively poor. Expert labeling of medical data is a bottleneck in the development of machine learning (ML) tools, and crowdsourcing has been demonstrated as a cost- and time-effi...
Background:
Despite the increasing ubiquity and accessibility of teledermatology applications, few studies have comprehensively surveyed their features and technical standards. Importantly, features implemented after the point of capture are often intended to augment image utilization, while technical standards affect interoperability with existin...
Background:
The rapid adoption of digital skin imaging applications has increased the utilization of smartphone-acquired images in dermatology. While this has enormous potential for scaling the assessment of concerning skin lesions, the insufficient quality of many consumer/patient-taken images can undermine clinical accuracy and potentially harm...
Artificial intelligence (AI) has shown promise in the analysis of images for detection of melanoma.¹ The number of available dermatology smartphone applications (“apps”) is rapidly growing and there is increasing interest in apps that provide diagnosis or triage of skin lesions.2, 3 A 2020 systematic review found that nine studies evaluating six ap...
Citations
... In most cases, the anatomical context of such images is lost due to the exclusion of surrounding structures, while the primary focus of the image is the lesion. Furthermore, with the rapid adoption of digital skin imaging applications, the utilization of smartphoneacquired images in dermatology have also increased proportionally [123]. While many studies have proposed methods to detect melanomas from inconsistent dermoscopy images, most of them produce localized results that cannot be used universally due to the acquisitive conditions they are trained on, such as isolated datasets and specific illumination conditions, etc. [124]. ...
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... Some of these instruments allow a faster and more accurate diagnosis of skin neoplasms, which is necessary to ensure adequate treatment of the patient. At the same time, they require specific, lengthy training and may increase costs to health systems if used inappropriately [131][132][133]. ...
