Inspiration
We were inspired by the patients that were facing the issue while going through the tests to detect cancer.
What it does
It is an early detection tool. That can detect the subtype and also the probability of it at a very early stage.
How we built it
Challenges we ran into
Challenges Faced By the Doctors It can be agonizing to wait for biopsy results (Depending on the type of evaluation needed) the next steps might take a few hours or several days. If the pathologist suspects certain types of cancer, he or she might need to perform additional testing to determine the subtype. This process takes an additional 24 to 96 hours, depending on the complexity of cancer. Tacking the list of patients and their status on the process is missing. Recording the data at a common repository to maintain centralized information storage of the patients is missing. Lack of awareness about among the women above the age of 40 about the importance of annual screening mammography.
Challenges Faced By the Patients Denial of the medical condition and irregular routine check-ups. Young patients when diagnosed with cancer may have to make important decisions about their treatment within a few days or weeks. While those decisions may help save their lives, they also come with long-term side effects that sometimes were not anticipated. Most of the women affected with breast cancer don't have moral support to call out for help in diagnosis. For example single or older women. This can be due to suppressing emotional and financial demands. Sometimes the patient is undergoing diagnosis for some other medical condition. This can act as a barrier in treating the patient in cancer-related treatments. For example, for an 85-year-old with multiple medical problems, dementia, or physical limitations, the recommendations for care and treatment become more complex. Development of new and chronic diseases in the patient who is undergoing cancer-related treatment.
Accomplishments that we're proud of
We have scoped both doctor centric and patient-centric solution We aim to speed up the process of obtaining biopsy test results by implementing a Convolutional Neural Network which is supplied with a dataset(both cancerous and healthy tissues) and the patient’s biopsy image. This will not only help us achieve a quicker diagnosis but also reduce the wait time of the patient. Doctors would now be able to get the current status of the patient being diagnosed. They will also have a list of patients that they have attended along with a brief idea about their medical history(that is fed in our database) through our portal.
What we learned
What's next for Hope. Strength. Love
Please refer to our video to know more about it.
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