From diagnosis to intervention: a review of telemedicine's role in skin cancer care.
Kayla D MashoudySofia M PerezKeyvan NouriPublished in: Archives of dermatological research (2024)
Skin cancer treatment is a core aspect of dermatology that relies on accurate diagnosis and timely interventions. Teledermatology has emerged as a valuable asset across various stages of skin cancer care including triage, diagnosis, management, and surgical consultation. With the integration of traditional dermoscopy and store-and-forward technology, teledermatology facilitates the swift sharing of high-resolution images of suspicious skin lesions with consulting dermatologists all-over. Both live video conference and store-and-forward formats have played a pivotal role in bridging the care access gap between geographically isolated patients and dermatology providers. Notably, teledermatology demonstrates diagnostic accuracy rates that are often comparable to those achieved through traditional face-to-face consultations, underscoring its robust clinical utility. Technological advancements like artificial intelligence and reflectance confocal microscopy continue to enhance image quality and hold potential for increasing the diagnostic accuracy of virtual dermatologic care. While teledermatology serves as a valuable clinical tool for all patient populations including pediatric patients, it is not intended to fully replace in-person procedures like Mohs surgery and other necessary interventions. Nevertheless, its role in facilitating the evaluation of skin malignancies is gaining recognition within the dermatologic community and fostering high approval rates from patients due to its practicality and ability to provide timely access to specialized care.
Keyphrases
- skin cancer
- palliative care
- healthcare
- artificial intelligence
- high resolution
- end stage renal disease
- newly diagnosed
- ejection fraction
- quality improvement
- machine learning
- randomized controlled trial
- deep learning
- soft tissue
- wound healing
- computed tomography
- primary care
- mental health
- mass spectrometry
- magnetic resonance
- atrial fibrillation
- climate change
- liquid chromatography
- patient reported
- convolutional neural network