Artificial intelligence in Dermatopathology.
Shishira R JartarkarClay J CockerellAnant D PatilMartin KassirMahsa BabaeiBeate Weidenthaler-BarthStephan GrabbeMohamad GoldustPublished in: Journal of cosmetic dermatology (2022)
Convolutional neural network, a type of deep neural network, is considered as an ideal tool in image recognition, processing, classification, and segmentation. Implementation of AI in tumor pathology is involved in the diagnosis, grading, staging, and prognostic prediction as well as in identification of genetic or pathological features. In this review, we attempt to discuss the use of AI in dermatopathology, the attitude of patients and clinicians, its challenges, limitation, and potential opportunities in future implementation.
Keyphrases
- artificial intelligence
- deep learning
- convolutional neural network
- machine learning
- big data
- neural network
- end stage renal disease
- primary care
- healthcare
- ejection fraction
- newly diagnosed
- chronic kidney disease
- quality improvement
- palliative care
- peritoneal dialysis
- lymph node
- genome wide
- prognostic factors
- current status
- patient reported
- patient reported outcomes
- climate change
- risk assessment