Development and prospective validation of an artificial intelligence-based smartphone app for rapid intraoperative pituitary adenoma identification.
Rabih Bou-NassifAnne S ReinerMatthew PeaseTejus BaleMarc A CohenMarc K RosenblumViviane TabarPublished in: Communications medicine (2024)
The app can be readily expanded and repurposed to work on different types of tumors and optical images. Rapid recognition of normal versus tumor tissue during surgery may contribute to improved intraoperative surgical management and oncologic outcomes. In addition to the accelerated pathological assessments during surgery, this platform can be of great benefit in community hospitals and developing countries, where immediate access to a specialized pathologist during surgery is limited.
Keyphrases
- artificial intelligence
- minimally invasive
- coronary artery bypass
- deep learning
- healthcare
- machine learning
- big data
- mental health
- patients undergoing
- palliative care
- convolutional neural network
- prostate cancer
- robot assisted
- skeletal muscle
- metabolic syndrome
- optical coherence tomography
- acute coronary syndrome
- coronary artery disease
- loop mediated isothermal amplification