expert system for ENT:sore-throat
Mar. 27th, 2008 11:44 am![[personal profile]](https://www.dreamwidth.org/img/silk/identity/user.png){kind=small}
guslInteracting with the real world (especially doctors) often makes me want to create expert systems.
Here's an idea for diagnosing allergy/cold/flu complaints. It should be fairly easy to set up a booth on campus, and collect data from volunteers (using Excel and a digital camera); call up 10 doctors, and have them diagnose the profiles given to them. Trying to get the ground truth would be more expensive, since that might involve blood tests (if that works!).
INPUTS (roughly ordered by presumed importance)
photograph of:
* face
* throat
* nose, ears, eyes
* complaints (possibly null)
* answer to "how long have you felt this way?", "do you have seasonal allergies?", and other relevant questions
* time of year, time of day when the data was collected
* biographical info: age, sex, height/weight, race
OUTPUT:
* probability distribution over {nothing, allergy, virus, post-nasal drip, sleep apnea, other} (optionally, allow multiple conditions)
We can control which inputs are given to doctors. My goal is to do machine learning, to automate the diagnostic process, by learning a function from the inputs (images and text) to the diagnosis.
I'm 99.9% sure that studies like this have been done before. How well did the system work?
Other possible applications of the statistics computed from this:
* help individual doctors correct their biases
* help individual doctors correct their incoherences
* help doctors make quicker decisions
* help patients select doctors who are good at diagnosing people with their type of profile
* for patients who want second opinions, help find an optimal pair of doctors (e.g. pairs whose biases would cancel out)
Here's an idea for diagnosing allergy/cold/flu complaints. It should be fairly easy to set up a booth on campus, and collect data from volunteers (using Excel and a digital camera); call up 10 doctors, and have them diagnose the profiles given to them. Trying to get the ground truth would be more expensive, since that might involve blood tests (if that works!).
INPUTS (roughly ordered by presumed importance)
photograph of:
* face
* throat
* nose, ears, eyes
* complaints (possibly null)
* answer to "how long have you felt this way?", "do you have seasonal allergies?", and other relevant questions
* time of year, time of day when the data was collected
* biographical info: age, sex, height/weight, race
OUTPUT:
* probability distribution over {nothing, allergy, virus, post-nasal drip, sleep apnea, other} (optionally, allow multiple conditions)
We can control which inputs are given to doctors. My goal is to do machine learning, to automate the diagnostic process, by learning a function from the inputs (images and text) to the diagnosis.
I'm 99.9% sure that studies like this have been done before. How well did the system work?
Other possible applications of the statistics computed from this:
* help individual doctors correct their biases
* help individual doctors correct their incoherences
* help doctors make quicker decisions
* help patients select doctors who are good at diagnosing people with their type of profile
* for patients who want second opinions, help find an optimal pair of doctors (e.g. pairs whose biases would cancel out)
![[identity profile]](https://www.dreamwidth.org/img/silk/identity/openid.png){kind=small}
(no subject)
Date: 2008-03-27 05:04 pm (UTC)(no subject)
Date: 2008-03-27 07:06 pm (UTC)(no subject)
Date: 2008-03-27 07:36 pm (UTC)(no subject)
Date: 2008-03-27 07:46 pm (UTC)(no subject)
Date: 2008-03-27 09:26 pm (UTC)