With the support of the United States and India Science and Technology Endowment Foundation (USISTEF) and Qualcomm
Design in India (QDIC), engineers from Alexapath developed a portable microscope system capable of taking glass Pap
Smear slides as an input and able to provide Computer Assisted Diagnosis (CAD). The CAD solution called AutoPap is able
to analyze the digitized mobile Whole Slide Image (mWSI)1 and determine whether or not there are abnormal cells present.
The microscope system - AiDA (Artificial intelligence Diagnostic Assistant) easily fits on any counter top and requires
no external wifi or expensive GPUs. The artificial intelligence is able to run on any device with a processor equal to
or better than the SnapDragon 820 chip. In order to succeed, the following four tasks were completed: 1- build a robotic
microscope capable of imaging glass slides, 2- develop software for acquisition and viewing of digitized glass slides,
3- create a Convolutional Neural Network (CNN) capable of classification and 4- deploy the software and Ai onto a
smartphone. The end to end solution including a microscope, camera, and smartphone is both portable and affordable. The
potential use for the system is akin to triage. With such a large number of women in India needing cervical cancer
screenings, a solution that can identify the presence of abnormal cells in pap smears and has a turn around time of less
than six minutes can prove a powerful ally - allowing human cytologists to only focus on the small number of cases
needing staging. Additionally since AutoPap functions as an “Assisted” Diagnosis, which does not require De Novo
classification, AutoPap maybe able to quickly enter the market. The work contained in this paper is the work of
Alexapath LLC with funding from the USISTEF and QDIC. There are no conflicts of interest to report.