Diabetic Retinopathy

More than 30.3 million people suffer from diabetes here in the United States. A quarter of them suffer from diabetic retinopathy, and this number is only growing.

Diabetic retinopathy (DR) is a retinal disease that affects patients with diabetes. It is currently diagnosed entirely by fundoscopic analysis but manual analysis of DR is time-consuming and not always accessible. Furthermore, early diagnosis of DR in its non-proliferative stage is difficult due to a lack of outward visible symptoms and patients failing to attend regular ophthalmology appointments, resulting in under diagnosis and the onset of advanced complications.

Diabetic retinopathy can lead to a number of complications in eyesight; patients may suffer from a vitreous hemorrhage leading into a macular edema. This may result in a partial loss of eyesight or blindness.

Between 40 to 45% of Americans diagnosed with diabetes have some stage of diabetic retinopathy and this disease accounts for at least 12% of all new annual cases of blindness in the United States alone

So what are we proposing?

Our Solution

By combining a hardware attachment to your average smartphone with a machine learning model trained to detect retinopathy, we hope to develop a device patients and optometrists can use to identify and monitor the onsset of retinopathy

Our camera module will consist of a lens system combined with an infrared focusing module that should be able to fit onto a smartphone. This will allow patients to use their phones as a basic fundoscope and then upload the image to our analysis platform as necessary.

For analysis of the captured images, a Convolutional Neural Network (CNN) will be used. A CNN operates by training on a large number of labeled images in order to extract important features that define a classification. After training the model, the CNN can then make predictions about the category of new input images.

Our team hopes to use this novel solution to make sure screening reaches those who need it most.

Our Team

MoLabs consists of experienced biomedical and software engineers with experience in research and device development from Google, Columbia University, The Icahn School of Medicine and the Leibniz Universität Hannover, Germany. Our team members have specialized in projects focusing on optics, stochastic modelling, circuit analysis, signal processing, computational biology, neuroscience, biomechanics and clinical research.

Please reach out to us!

Gaining Traction

We're excited to share our current progress and success with drCAM. Please check back in for periodic updates!

Columbia Fast Pitch

Fast pitch winners photo

November 14, 2018

MoLabs recently unveiled drCAM for the first time at Columbia University's Fast Pitch Competition! Fast Pitch is Columbia Engineering Entrepreneurship's annual elevator pitch competition where teams have 60 seconds to sell their business ideas to a panel of judges. drCAM was awarded First Place and $1300 in funding, along with the Audience Choice Award.

Results

News Article

Cisco Global Problem Solver Challenge 2018

Cisco Challenge logo

February 19, 2018

MoLabs competed in the Cisco Global Problem Solver Challenge, and has been selected as a semifinalist! The Challenge aims to recognize innovative solutions that leverage technology for social impact from student entrepreneurs around the world. Close to 300 teams submitted their ideas and only 33 have been invited to continue in the challenge. MoLabs is excited to continue perfecting our design and hopes to progress to the finalist stage soon!

Results

Almaworks

Almaworks logo

February 21, 2018

Almaworks, the startup accelerator program run by the Columbia Organization of Rising Entrepreneurs, has selected Molabs for its Spring 2018 cohort. Over the course of the 8 week program, we will learn from experienced mentors on how to achieve significant, sustainable growth. We are grateful for this opportunity and can't wait to leverage our knowledge from the program in improving our device.

More information

Rice 360° Global Health Technologies Design Competition

Rice 360 logo

February 21, 2018

Come watch MoLabs present at Rice University on March 23rd! The Rice 360° Eighth Annual Undergraduate Global Health Technologies Design Competition will feature over 20 student teams from national and international universities who will present their low-cost global health technologies. Entries will be judged on the quality of the problem definition, the effectiveness and potential impact of the design solution, and the likelihood that the solution can be successful in improving healthcare delivery in low-resource settings by faculty, clinicians, and private and public sector partners from around the country.

More information

Contact

In order to present the best possible product for patients and doctors, we welcome any and all feedback, collaboration requests or information on funding opportunities. Please reach out!
If you want to stay up to date on our endeavors, please follow us!

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