Stimulated Raman Histology and Machine learning provides an alternative approach in brain tumor diagnosis

The study published in Nature Medicine examined the diagnostic accuracy of brain tumor image classification through artificial intelligence tool, compared with the accuracy of pathologist interpretation of conventional histologic images. The results for both methods were comparable: the artificial intelligence based diagnosis was 94.6% accurate, compared with 93.9% for the traditional pathologist-based assessment and interpretation. … Continue reading Stimulated Raman Histology and Machine learning provides an alternative approach in brain tumor diagnosis