Iris Diabetes Detection using SVM classifier

2 Ansichten (letzte 30 Tage)
Hazel Sialongo
Hazel Sialongo am 25 Sep. 2016
Beantwortet: Star Strider am 25 Sep. 2016
I want to detect diabetes by classifying it using SVM. How will I do that?
  1 Kommentar
John D'Errico
John D'Errico am 25 Sep. 2016
Bearbeitet: John D'Errico am 25 Sep. 2016
Ask your teacher. That is why they are there. Anyway, you were given the assignment, not us. As well, this is not even a MATLAB question. So do some reading. And get to work.

Melden Sie sich an, um zu kommentieren.

Antworten (1)

Star Strider
Star Strider am 25 Sep. 2016
By the time patients with diabetes mellitus (DM) develop changes detectable by pupillomerty, they probably already know, since delayed pupillary reflexes are characteristic of advanced diabetic autonomic neuropathy. A brief PubMed search this morning returned several hundred citiations, of which a few of what appear to me to be the more relevant are in the attached text file.
Consult with an ophthalmologist and diabetologist in your university, then a statistician, and decide then what data to gather and how to gather it with the instrumentation available to you, then how best to classify your patients based on the data you gather. You will of course need other laboratory tests relevant to determining the severity of DM and specifically autonomic neuropathy, including heart rate variability, postural blood pressure changes, HbA1c, fasting glucose, renal function, and others.
I leave you to it!
Have fun!

Kategorien

Mehr zu Statistics and Machine Learning Toolbox finden Sie in Help Center und File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by