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
- surgical site infection
- mental health
- prostate cancer
- type diabetes
- palliative care
- adipose tissue
- convolutional neural network
- skeletal muscle
- loop mediated isothermal amplification
- optical coherence tomography
- mass spectrometry
- coronary artery disease
- sensitive detection
- high speed