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AI-POWERED PAP SMEAR SCREENING
Cancerous
Squamous metaplasia
How It Works
01
FAST
PapSamurAI is a portable Pap smear diagnostic tool for Gynaecologists that will bring the screening results of a pap smear sample in less than 10 minutes to classify as cancerous cervical cells or not. This will highly speed-up the traditional process of smear sample analysis at a pathologist lab being used presently, which usually takes more than seven days to get the pap smear results.
02
ACCURATE
Our Research and Development that empowers PapSamurAI's Artificial Intelligence algorithms promises State-of-the-Art accurate results delivering 95% test accuracy which is more than 20% improvement over the existing traditional pathologist techniques. This will result in reduction of False Positives (Type I error) and more importantly False Negatives (Type II error).
03
EASY
Just mount your fixed pap smear sample to our device and the app will deliver the results within minutes. It is easy to implement in the Gynaecologist's office as it is a portable, affordable, and integrates with existing infrastructure making it a scalable Pap smear diagnostic system to deliver cytopathologic results immediately at the place of the sample extraction itself.
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Meet PapSamurAI
OUR STORY
We are a team of young, ambitious and talented researchers from the deep learning and the medical field who are on a mission to revolutionize the medical diagnosis industry starting with Cervical Cancer screening which is the fourth-most common cause of cancer & death due to cancer in women worldwide. About 70% of cervical cancers and 90% of deaths occur in developing countries.
OUR VISION
Cervical cancer is 100% preventable as it typically develops from precancerous changes over 10 to 20 years, period on which it can be detected in the regular gynecological checks by the Pap smear test. PapSamurAI proposes a Point-of-Care (POC) Pap smear diagnostic system to provide an affordable, scalable solution that leverages existing smartphone infrastructure to improve cervical cancer screening.
TECHNOLOGY
PapSamurAI's underlying technology consists of a POC Hardware which is essentially a smartphone based digital microscope that acquires high-resolution stained pap smear image which is analysed by our proprietary Computer Vision and EdgeAI technology based Software delivering state-of-the-art accurate results in a matter of minutes, right on the device. Our solution delivers results without internet or Cloud computing.
Meet The Team
Pranshul Sardana
Pranshul is an incoming doctoral student at Purdue University. In his Ph.D., he will be developing the next generation of diagnostic devices based on experimental fluid dynamics and deep learning. He has 7 publications in journals and conferences like Springer and IEEE as well as won various hackathons & international business competitions in India, Malaysia, & Germany, bringing about tech-advancements from research labs to the real-world. He holds an M.Sc. in Microsystems Engineering from Uni-Freiburg and completed his thesis at Hahn-Schickard.
Clara Labonia
Clara is an MD pursuing a PhD in Drug Innovation and Nanomedicine at the University Medical Hospital of Utrecht, in The Netherlands. During her medical practices she did a rotation at the Service of Gynecology at San Gerardo Hospital in Italy. She did an International Master in Biomedical Sciences at the University of Freiburg in Germany, and her Master´s Thesis consisted of bioprinting prevascular structures of multiple cell types, at the Institute of Microsystems Engineering of Freiburg, Germany.
Mohit Kalra
Mohit is a Computer Science Grad student at University of Stuttgart, specializing in Artificial Intelligence. Being a Director of a successful Engineering Firm in India, for 8+ years, he is now venturing into Deep-Tech Startups. Since 2017, he has been awarded several accolades for various Startup Competitions and Business Challenges at European and Global level. Academically, he has carried out research in Medical IoT, Embedded Robotics, Computer Vision and Deep Learning at Fraunhofer IPA and Edge Case Research
Manav Madan
Manav is from Delhi, India. He is a Software Developer currently pursuing a Master's degree in Embedded Systems at the University of Freiburg. He has been working in Deep learning and machine learning during the last two years at Fraunhofer Institute for Physical Measurement Techniques (IPM) on anomaly detection in multi-perspective scenario with focus on working with less data. His main interest is using Deep Learning for unsupervised machine learning tasks. He holds a BEng degree in Electrical and IT engineering from Hochschule Ravensburg-Weingarten.
Victor George
Victor is a graduate student majoring in Computer Science at University of Freiburg. His regions of interests include Control System applications involving deep reinforcement learning, pattern recognition and firmware development. He was an Embedded systems engineer specializing in IoT and automotive domain with stints at Robert Bosch, the start-up Tagbox in his previous life. With a Bachelors in Electrical Engineering, he is currently taking a detour to explore software development and data science. Besides, he is also a student assistant at Data science firm Psiori Gmbh
Partners
University of Stuttgart
University Medical Center Utrecht
University of Freiburg
Purdue University
Testimonials
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