title: Diagnostic inaccuracy of smartphone applications for melanoma detection.
abstract: OBJECTIVE
  To measure the performance of smartphone applications that evaluate photographs of skin lesions and provide the user with feedback about the likelihood of malignancy.
  
  
  METHODS
  Case-control diagnostic accuracy study.
  
  
  METHODS
  Academic dermatology department. PARTICIPANTS AND MATERIALS: Digital clinical images of pigmented cutaneous lesions (60 melanoma and 128 benign control lesions) with a histologic diagnosis rendered by a board-certified dermatopathologist, obtained before biopsy from patients undergoing lesion removal as a part of routine care.
  
  
  METHODS
  Sensitivity, specificity, and positive and negative predictive values of 4 smartphone applications designed to aid nonclinician users in determining whether their skin lesion is benign or malignant.
  
  
  RESULTS
  Sensitivity of the 4 tested applications ranged from 6.8% to 98.1%; specificity, 30.4% to 93.7%; positive predictive value, 33.3% to 42.1%; and negative predictive value, 65.4% to 97.0%. The highest sensitivity for melanoma diagnosis was observed for an application that sends the image directly to a board-certified dermatologist for analysis; the lowest, for applications that use automated algorithms to analyze images.
  
  
  CONCLUSIONS
  The performance of smartphone applications in assessing melanoma risk is highly variable, and 3 of 4 smartphone applications incorrectly classified 30% or more of melanomas as unconcerning. Reliance on these applications, which are not subject to regulatory oversight, in lieu of medical consultation can delay the diagnosis of melanoma and harm users.
authors: University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA.
authors: Joel A
authors: JA
authors: Wolf
authors: Jacqueline F
authors: JF
authors: Moreau
authors: Oleg
authors: O
authors: Akilov
authors: Timothy
authors: T
authors: Patton
authors: Joseph C
authors: JC
authors: English
authors: Jonhan
authors: J
authors: Ho
authors: Laura K
authors: LK
authors: Ferris
mesh_terms: D000465:Algorithms; D040421:Cell Phone; D034201:Computers, Handheld; D046169:Dermoscopy; D003937:Diagnosis, Differential; D003951:Diagnostic Errors; D034742:Electronic Mail; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008545:Melanoma / Q000175:diagnosis*; D012372:ROC Curve; D012878:Skin Neoplasms / Q000175:diagnosis*; D012984:Software; D017216:Telemedicine / Q000295:instrumentation*; D014584:User-Computer Interface; D014741:Video Recording / Q000379:methods