Netrascopy

Diabetic Retinopathy (DR) is a complication of diabetes that causes the blood vessels of the retina to swell and leak fluids and blood, potentially leading to vision loss in advanced stages. DR is a leading cause of blindness in the working-age population of developed countries, affecting over 93 million people globally. In the United States, it is estimated that 29.1 million people have diabetes, and around 40-45% of those individuals have some stage of DR. In India, 16 out of every 200 people are formally diagnosed with mild DR, making it one of the most common diseases in the country. However, due to a lack of awareness, proper infrastructure, and affordability, many patients are not diagnosed with diabetes until later stages, often through the use of invasive methods such as blood tests, which also increases the risk of acquiring Transfusion-transmitted infections (TTIs). This delay in diagnosis can exacerbate the disease, making it more difficult to treat without high volumes of medication.

Currently, detecting DR is a time-consuming and manual process that requires a trained clinician to examine digital color fundus photographs of the retina. The results of these evaluations are often delayed by a day or two, leading to lost follow up, miscommunication, and delayed treatment. As the number of individuals with diabetes continues to increase, the infrastructure needed to prevent blindness due to DR will become increasingly inadequate. 

Furthermore, current methods of diagnosis and monitoring are not financially accessible for many patients, as they require frequent visits to healthcare providers. There is a significant demand among diabetes patients for an automated DR diagnosis kit that can be used at home to track the progression of the disease over time.

Our innovation is a kit for the early detection of diabetic retinopathy through the analysis of fundus images, which are digital color photographs of the retina. We have developed a specialized self-diagnosis kit that consists of a fundus camera that allows patients to take clear videos and photos of their fundus, a Pasteur-pipette-of-Tropicamide (eye drop bottle), which is a liquid patient will have to put into their eyes to dilate the retina before taking pictures and video, and a manual explaining how to use the kit. After dilating the retina using tropicamide the user will open the Netra mobile application which is an app that consists of pre-optimized settings to suit mobile cameras to be able to take clear and detailed FUNDUS images, after taking images and videos of their retina. These images and videos are uploaded to our web application, which analyzes them using a convolutional neural network to determine whether the patient has diabetes. The data is first transferred to our Frames API, which breaks the video into individual frames and uploads them to a server. The links to these images are then fetched and sent to our Flask API one by one, which acts as a communication bridge between the web application and the machine learning model. The machine learning model, a ResNet50 model trained on a dataset of 35,000 images, labels each image as one of the multiple stages of diabetic retinopathy i.e. No DR, Mild DR, Moderate DR, Severe DR, proliferative DR, after results of all the 30 test cases are received. The results are then transferred back to the web application and displayed to the patient based on a majority rule.

One of the key-innovations of our system is the use of a convolutional neural network for the analysis of fundus images and the low-cost easy-to-use fundus camera. Convolutional neural networks are widely used in medical image analysis due to their high effectiveness, and our ResNet50 model has achieved an accuracy of 95% and a validation loss score of 0.01, which is higher than the recent best algorithms trained on the same dataset. The use of a machine learning model also allows for more efficient and accurate diagnosis, as the manual process of evaluating fundus photographs by a clinician is prone to misdiagnosis and can be time-consuming.

Our system meets a number of needs and resolves several pain points for both individual users and the healthcare system as a whole. For individual users, our system provides a quick and convenient way to determine their risk of diabetes and DR, allowing them to take steps to prevent or manage the condition before it progresses to a more advanced stage. For the healthcare system, our system helps to reduce the burden of manual evaluation of fundus photographs and allows for more efficient and accurate diagnosis, ultimately leading to better treatment outcomes and a reduction in the risk of vision loss, it also reduces the overall cost of healthcare service delivery for diabetic retinopathy patients.
Website:https://netrascopy.com
App:https://netrascopy.onrender.co...
Research-Paper:https://shorturl.at/hyDGI

Our customers for the diabetic retinopathy kit are individuals at risk of or diagnosed with diabetes, as well as healthcare providers such as ophthalmologists and primary care physicians. Our target segments include individuals with type 1 and type 2 diabetes, as well as those with prediabetes. These individuals are concerned with maintaining good eye health, preventing or slowing the progression of diabetic retinopathy, and preserving their vision. They value quick, convenient, and accurate methods of diagnosis and monitoring their condition.

The size of the opportunity in the market for diabetic retinopathy detection is significant. According to the World Health Organization, as of 2021 there were approximately 463 million people living with diabetes worldwide, and this number is expected to increase to 700 million by 2045. Diabetic retinopathy is a common complication of diabetes and can lead to vision loss if left untreated, making early detection and management crucial. The burden of diabetes on the healthcare system is also significant, with direct and indirect costs estimated at over $760 billion per year globally.

The buyer or payer for our kit may be different from the customer, as it is likely that healthcare providers or insurance companies will purchase the kit for use by their patients or clients. However, individual customers may also purchase the kit directly from our website or through a retail partner.

The industry ecosystem for diabetic retinopathy detection includes a range of stakeholders such as healthcare providers, insurance companies, government regulatory bodies, and patient advocacy groups. These stakeholders are concerned with ensuring that effective and reliable methods of detection and management are available, as well as reducing the overall burden of diabetes on the healthcare system. Our kit fits into this ecosystem as a low-cost, convenient, and accurate method of detecting and monitoring diabetic retinopathy.

Arshroop learned about diabetic retinopathy through the experiences he had with his grandmother suffering from proliferated DR, upon further research he discovered that it disproportionately affects rural Indians without access to proper healthcare. Determined to find a solution, he met Atharv at the New York Academy of Science's Fall-Challenge (which they won). Arshroop also participated in "The Knowledge Society," where he met Ansh.

Our team is uniquely qualified to address this issue due to our experiences in healthcare and entrepreneurship. Arshroop has received India's highest civilian honor for his research on advancements in healthcare industries, and has conducted research at Harvard Medical School under Professor Ravi Jasuja. Atharv has won the world's largest student entrepreneurship competition, and has received $3,000 in funding for his projects. Ansh has conducted research on CRISPR and AI with researchers from Caltech and UC Irvine for over a year. We have valuable connections with government officials, professors at top universities, and healthcare professionals.

Testing our product has been a crucial step in development of our product, which has offered us insightful information about its functionality and efficacy. In our case, we tested our solution on 80 individuals, which was made possible by thorough surveys that we conducted with the support of the Centre for Sight hospitals in Indore. This sample size is considerable and enables us to compile a wide range of information and customer feedback on the effectiveness of the product.

A crucial step in product development is testing a product, which offers insightful information about its functionality and efficacy. In our case, we tested our solution on 80 individuals, which was made possible by thorough surveys that we conducted with the support of the Centre for Sight hospitals in Indore. This sample size is considerable and enables us to compile a wide range of information and customer feedback on the effectiveness of the product.

Through the recommendation of my grandfather, who is connected to the hospital, we have also received two orders from ophthalmologists working there. This is an important accomplishment since it shows that medical professionals are beginning to recognise and embrace our product. These orders also give us the chance to get more ophthalmologist input, which will help us further develop and enhance our product.

While the creation of a fundus camera for diabetic Indian patients is a challenging endeavour that calls for substantial subject knowledge and skill. We require the assistance of knowledgeable mentors who have expertise creating comparable medical equipment and technologies in order to make sure the product is dependable, precise, and specifically suited for Indians living in tier 2 and tier 3 towns and villages. These mentors can offer insightful advice on the functionality, features, and design that the fundus camera should have to accommodate diabetic Indian patients.

Along with receiving professional guidance, we also need to raise money to gather retinal imaging data from diabetic Indian patients. The algorithms that will be utilised in the fundus camera to detect and diagnose diabetic retinopathy must be trained on and improved upon using this data. The product might not operate at its best and might not be accurate enough to be helpful in identifying and treating diabetic retinopathy in Indian patients without a sizable and diverse dataset of Indian patients.
As a result, our project's success depends on having access to funding for data collecting as well as the support of knowledgeable mentors. With their assistance, we can make sure that our solution is especially designed to meet the needs of Indian patients and has the precision and dependability needed to have a significant influence on the detection and management of diabetic retinopathy in India.

The deployment of our finished fundus camera set to rural clinics, particularly in places like Aligarh, where the local government has specific incentive programmes in line with our healthcare goal, is our impact target for the upcoming year. In these underserved regions, where there is little access to high-quality eye care and the disease burden is substantial, our goal is to identify and treat diabetic retinopathy.

In order to accomplish this, we intend to work in conjunction with the Indian Institute of Technology Drishti CPS Foundation, a CSR programme run by the Indian government, to finish our research, development, and data collection. Through this partnership, we will have access to the tools and knowledge we need to hone and enhance our product and guarantee that it satisfies the requirements of diabetic Indian patients residing in tier 2 and tier 3 towns and villages.
We want to have a greater impact over the next five years by reaching more rural clinics in India and distributing our fundus camera set there. Our goal is to make our product more readily available to diabetic individuals who are at risk of developing diabetic retinopathy. In order to obtain additional information and data for ongoing product improvement, we also hope to work with more medical institutions and specialists.
In order to meet our impact target for the next five years, we intend to keep working with the Indian Institute of Technology Drishti CPS Foundation and look for alliances with other businesses and institutions that support our mission of enhancing rural India's access to high-quality eye care. In order to investigate additional features and functionalities that could improve the accuracy and efficacy of our product, we also want to increase our research and development efforts.

Indicators we are using to measure our progress: If our solution - Netra Kit - is affordable and reachable to the remotest villages in India. Accuracy: Is our deep learning model producing reliable results? Feasibility: Will our kit be user-friendly so that even an illiterate person could easily operate it?

One of the key innovations of our system is the use of a convolutional neural network for the analysis of fundus images and the low-cost easy-to-use fundus camera, which has been 3D printed from ABS (a low-cost plastic, perfect for prototypes and functional parts that do not require strength or heat resistance), and our ResNet50 model has achieved an accuracy of 95% and a validation loss score of 0.01, which is higher than the recent best algorithms trained on the same dataset. ML model works on the wisdom of crowd statistical methods. It measures the euclidean distance between various weights of machine learning algorithms, and clusters them, which increases the accuracy. We have the first movers advantage as well as intellectual property advantage. Which can help us differentiate ourselves from our almost non-existent current and potential competitors.Which means that we are more accurate as well as exponentially more efficient and affordable than our competitors. That is why we are placed on the top in the current DR detection market in terms of accuracy and affordability. And to conclude Our team understands the problem that we are targeting as we have firsthand seen people who have faced these problems. Our product specifically targets the pain points of our customers which have been extracted from various surveys and research. Our product has sustainable competitive advantage of intellectual property and first mover advantage, which can help us differentiate ourselves from our competitors in the long term. Our product has shown product market fit, clinically implementable accuracy, trust of users, and capability by raising 1000s of dollars in funding and testing at our local hospitals, getting feedback from patients and already getting contracts for large scale distributions. With all this we are set to change the lives of people who see dreams but can’t really see.

Our innovation is a kit for the early detection of diabetic retinopathy through the analysis of fundus images, which are digital color photographs of the retina. We have developed a specialized self-diagnosis kit that consists of a fundus camera that allows patients to take clear videos and photos of their fundus, a Pasteur pipette of Tropicamide (eye drop bottle), which is a liquid patient will have to put into their eyes to dilate the retina before taking pictures and video, and a manual explaining how to use the kit. After dilating the retina using tropicamide the user will open the Netra mobile application which is an app that consists of pre-optimized settings to suit mobile cameras to be able to take clear and detailed FUNDUS images, after taking images and videos of their retina. These images and videos are uploaded to our web application, which analyzes them using a convolutional neural network to determine whether the patient has diabetes. The data is first transferred to our Frames API, which breaks the video into individual frames and uploads them to a server. The links to these images are then fetched and sent to our Flask API one by one, which acts as a communication bridge between the web application and the machine learning model. The machine learning model, a ResNet50 model trained on a dataset of 35,000 images, labels each image as one of the multiple stages of diabetic retinopathy i.e. No DR, Mild DR, Moderate DR, Severe DR, proliferative DR, after results of all the 30 test cases are received. The results are then transferred back to the web application and displayed to the patient based on a majority rule.

In terms of impact, our innovation has the potential to greatly benefit both individual users and humankind as a whole. By enabling early detection of Diabetic Retinopathy, our system can help to prevent or slow the progression of these conditions by up to 95% (golden standard for early detection AI algorithms), ultimately leading to better health outcomes and a reduction in the overall burden of diabetes on the healthcare system. In terms of quantitative impact, our system has the potential to reach over 93 million users worldwide, given the high prevalence of diabetes and the limited availability of trained clinicians for the evaluation of fundus photographs.

Our team members come from different parts of India and have different educational and professional backgrounds. We believe that diversity in our team is our strength, and it helps us to design solutions that are culturally appropriate and relevant to the communities we serve.

As we continue to grow and expand our work, we recognize the importance of actively working towards becoming more diverse, equitable, and inclusive. We aim to create a work environment that is welcoming, respectful, and supportive of all team members, regardless of their background. We are committed to building a team that reflects the diversity of the communities we serve and to ensuring that all team members have equal opportunities for growth and advancement.

To achieve these goals, we have taken several actions. We have actively recruited team members from diverse backgrounds, and we prioritize the inclusion of underrepresented groups in our hiring process. We have also created a work environment that values and supports diverse perspectives and encourages open communication. We encourage team members to share their ideas and feedback freely, creating an inclusive culture that embraces constructive criticism.

In addition to these efforts, we also collaborate with organizations and programs that promote diversity and inclusion. Our team members participate in events and programs that support underrepresented groups in science, technology, engineering, and mathematics (STEM) fields. We believe that these collaborations help us to learn from and contribute to the larger community working towards diversity, equity, and inclusion.

In conclusion, our team is committed to promoting diversity, equity, and inclusion in our work. We actively seek to establish an inclusive work environment that values and supports all team members because we believe that a varied workforce may bring new ideas and solutions to our work. We will continue to prioritize diversity and inclusion in our hiring and partnership initiatives, and we remain dedicated to working towards a more equitable and inclusive world.

Our key revenue streams come from the sale of our diabetic retinopathy detection kit to consumers and healthcare providers. Our pricing is based on the cost of materials and manufacturing. We aim to offer our kit at a competitive price that is accessible to a wide range of patients. The cost of materials and manufacturing for one unit of our kit is $12, and based on feedback from over 200 potential customers, we believe that the market is willing to pay $20-30 per unit. In addition, we incur marketing costs as we promote and sell our kit. 

To deliver one unit of our kit, we use the API's of pre-existing delivery companies. Once the manufacturing and packaging of an order is completed, it will be received by an existing delivery operator (delivery boy, truck, etc.) who will deliver it to the end user. These costs include the cost of materials and manufacturing, as well as any transportation or logistics costs associated with delivering the kit to the customer. Currently, we are using the Delhivery API service to deliver our product to our initial customers, and all manufacturing is done manually by us in India to further reduce costs. After including the cost of goods sold (COGS), customer acquisition cost (CAC), and our profit of 33%, the end selling price comes out to be $20 plus the annual quarterly subscription cost (most likely $5, still discussing) for web application.

Overall, our business model is designed to generate revenue by selling our kit at a price that covers our costs and generates a profit, while also considering the customer's ability to pay and concerns. By focusing on marketing and sales efforts and expanding our distribution partnerships, we believe that we can drive strong revenue growth and achieve a sustainable and profitable business.

Our current plan for becoming financially sustainable involves a combination of strategies. The main source of income for us is winning entrepreneurial competitions, which we have been successful at in the past, including winning the second prize in the Business and Innovation track at the Diamond Challenge. We will continue to participate in such competitions to secure funding for our work.

We are also in talks with the IITI Drishti CPS Foundation, who have shown interest in providing us with lab space and equipment for our research and development. This partnership would help us save on research and development costs, thereby contributing to our financial sustainability.

Furthermore, we plan to take on contracts from hospitals during the development phase of our product, which would generate additional revenue for us. This will also provide us with the opportunity to test and improve our product in a real-world setting.

In the long term, our revenue streams will need to cover our expected expenses. We plan to achieve this by selling our product once it is fully developed and ready for deployment. We will also explore opportunities to provide services related to our product, such as maintenance and training.

Additionally, we will consider raising investment capital in the future to further scale our operations. However, our primary focus right now is on developing a sustainable business model and generating revenue through our product and services.

Overall, our plan for becoming financially sustainable involves a combination of winning entrepreneurial competitions, partnerships with organizations such as IITI Drishti CPS Foundation, taking on contracts from hospitals, selling our product, and providing related services. We believe that by diversifying our revenue streams, we will be able to sustain our operations in the long term.

List of organizations that fundes us through winning competitions
University of Delaware Diamond Challenge: $8,500
Blue Learn Pitch Tank: $3,000
Indian Institute of Technology Techfest, Bombay: $1,000
IITI Drishti CPS Foundation: $500