by omidoft » Tue Feb 12, 2019 02:25 pm
I develop a machine learning tool to speed up the generation of reports to radiologists, improving the accuracy of MRI imaging analysis.
The goal of our development is to detect cancer in the early stages when the survival rate of patients reaches 90%. This will reduce the number of insurance claims and allow to offer a better price for insurance.
Machine learning makes it possible:
- to reduce the routine and reduce the average time to prepare a report (potentially 2 times)
- 85% increase in the accuracy of diagnosis of cancer in the early stages and increase the survival of cancer patients
- to reduce the number of insurance claims
- to generate part of the report programmatically and highlight potential areas of the tumor, reducing the time of analysis of the image
I want to find out if there are any problems with the accuracy of cancer diagnosis, increasing the competitiveness of the clinic, reducing the number of medical errors. To do this, I composed several questions:
If you are an insurance agent:
If you are a radiologist:
If you are the chief doctor:
Your answers will help us choose the right direction of research and follow them really in demand.
The goal of our development is to detect cancer in the early stages when the survival rate of patients reaches 90%. This will reduce the number of insurance claims and allow to offer a better price for insurance.
Machine learning makes it possible:
- to reduce the routine and reduce the average time to prepare a report (potentially 2 times)
- 85% increase in the accuracy of diagnosis of cancer in the early stages and increase the survival of cancer patients
- to reduce the number of insurance claims
- to generate part of the report programmatically and highlight potential areas of the tumor, reducing the time of analysis of the image
I want to find out if there are any problems with the accuracy of cancer diagnosis, increasing the competitiveness of the clinic, reducing the number of medical errors. To do this, I composed several questions:
If you are an insurance agent:
- Would you offer insurance on more favorable terms if doctors could reduce the number of medical errors through the use of machine learning?
Could you offer a more competitive price of insurance, provided that the clinic uses software with machine learning of proven effectiveness?
If you are a radiologist:
- How often are your clients screened for cancer?
How much time does it take to describe pictures for one patient? How many patients pass per day?
Which items in the report take the most time?
If you are the chief doctor:
- How often do you receive complaints from patients to diagnose cancer with an MRI?
Would your clinic be able to serve more people per day by reducing the time for a single person, or do you have a limited number of patients?
Does reducing the number of medical errors affect the price of insurance for doctors and the clinic as a whole, or is it fixed?
Your answers will help us choose the right direction of research and follow them really in demand.
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