A smartphone‐based standalone fluorescence spectroscopy tool for cervical precancer diagnosis in clinical conditions
Shivam Shukla, Bhaswati Singha Deo, Chaitanya Vishwakarma, Subrata H. Mishra, Shikha Ahirwar, Amar Nath Sah, Kiran Pandey, Sweta Singh, S. N. Prasad, Ashok Kumar Padhi, Mayukha Pal, Prasanta Kumar Panigrahi, Asima Pradhan · Journal of Biophotonics · 2024
Real-time prediction about the severity of noncommunicable diseases like cancers is a boon for early diagnosis and timely cure. Optical techniques due to their minimally invasive nature provide better alternatives in this context than the conventional techniques. The present study talks about a standalone, field portable smartphone-based device which can classify different grades of cervical cancer on the basis of the spectral differences captured in their intrinsic fluorescence spectra with the help of AI/ML technique. In this study, a total number of 75 patients and volunteers, from hospitals at different geographical locations of India, have been tested and classified with this device. A classification approach employing a hybrid mutual information long short-term memory model has been applied to categorize various subject groups, resulting in an average accuracy, specificity, and sensitivity of 96.56%, 96.76%, and 94.37%, respectively using 10-fold cross-validation. This exploratory study demonstrates the potential of combining smartphone-based technology with fluorescence spectroscopy and artificial intelligence as a diagnostic screening approach which could enhance the detection and screening of cervical cancer.