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Artificial intelligence in
Dermatology: A boon or Threat
Dr. Siddhartha Dash
Assistant Professor
SCBMCH, Cuttack
AI Application in Dermatology
ULCER ASSESSMENT
MEASURING PRECISE
WOUND BOUNDARIES
Sensitivity: 87.3%
Specificity: 95.7%
ABILITY TO
CLASSIFY
GRANULATION,
SLOUGH AND
NECROTIC TISSUE
Accuracy: 87.61%
PREDICTION OF RISK
TO DEVELOP
PRESSURE ULCERS
Gomolin A, Netchiporouk E, Gniadecki R, Litvinov IV. Artificial Intelligence Applications in
Dermatology: Where Do We Stand? Front Med (Lausanne). 2020 Mar 31;7:100.
INFLAMMATORY DISORDERS
ATOPIC DERMATITIS
• EHR based phenotyping
to identify AD patients
• To detect AD skin vs
unaffected skin
PSORIASIS
• To classify the severity
of psoriasis lesions
• Predict psoriasis patient
responses to biologic
therapy
OTHERS
• Grading and classification of acne
lesions
• Differentiate several
papulosquamous diseases such as
psoriasis, seborheic dermatitis,
lichen planus, pityriasis, and
chronic dermatitis
Gomolin A, Netchiporouk E, Gniadecki R, Litvinov IV. Artificial Intelligence Applications in
Dermatology: Where Do We Stand? Front Med (Lausanne). 2020 Mar 31;7:100.
The AI‐integrated health service of the
future?
Two main scenarios:
• Direct to consumer or public
• Decision aid for clinicians
Du-Harpur X, Watt FM, Luscombe NM, Lynch MD. What is AI? Applications of artificial
intelligence to dermatology. Br J Dermatol. 2020 Sep;183(3):423-430.
Du-Harpur X, Watt FM, Luscombe NM, Lynch MD. What is AI? Applications of artificial
intelligence to dermatology. Br J Dermatol. 2020 Sep;183(3):423-430.
Artificial intelligence in Dermatology.pptx

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Artificial intelligence in Dermatology.pptx

  • 1. Artificial intelligence in Dermatology: A boon or Threat Dr. Siddhartha Dash Assistant Professor SCBMCH, Cuttack
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11. AI Application in Dermatology
  • 12.
  • 13. ULCER ASSESSMENT MEASURING PRECISE WOUND BOUNDARIES Sensitivity: 87.3% Specificity: 95.7% ABILITY TO CLASSIFY GRANULATION, SLOUGH AND NECROTIC TISSUE Accuracy: 87.61% PREDICTION OF RISK TO DEVELOP PRESSURE ULCERS Gomolin A, Netchiporouk E, Gniadecki R, Litvinov IV. Artificial Intelligence Applications in Dermatology: Where Do We Stand? Front Med (Lausanne). 2020 Mar 31;7:100.
  • 14. INFLAMMATORY DISORDERS ATOPIC DERMATITIS • EHR based phenotyping to identify AD patients • To detect AD skin vs unaffected skin PSORIASIS • To classify the severity of psoriasis lesions • Predict psoriasis patient responses to biologic therapy OTHERS • Grading and classification of acne lesions • Differentiate several papulosquamous diseases such as psoriasis, seborheic dermatitis, lichen planus, pityriasis, and chronic dermatitis Gomolin A, Netchiporouk E, Gniadecki R, Litvinov IV. Artificial Intelligence Applications in Dermatology: Where Do We Stand? Front Med (Lausanne). 2020 Mar 31;7:100.
  • 15.
  • 16.
  • 17.
  • 18. The AI‐integrated health service of the future? Two main scenarios: • Direct to consumer or public • Decision aid for clinicians Du-Harpur X, Watt FM, Luscombe NM, Lynch MD. What is AI? Applications of artificial intelligence to dermatology. Br J Dermatol. 2020 Sep;183(3):423-430.
  • 19. Du-Harpur X, Watt FM, Luscombe NM, Lynch MD. What is AI? Applications of artificial intelligence to dermatology. Br J Dermatol. 2020 Sep;183(3):423-430.