I came here because I needed to sort out the concept of Sensitivity vs Specificity wrt machine learning. This video is perfect for that. The proportion of TP (True positives) classified correctly is sensitivity, the proportion of true negatives classified correctly is specificity. Very succinct, thank you.
You delivered as you promised... I was calculating my sister's APRI score and I found these two terms there... And now I recall that I found these terms on glucometer leaflet and covid rapid test kits and ecocardiogram vs angiography studies.... Thanks
Thank you for the video. It was helpful for my purposes. I was a little surprised to see that possible harm to someone who is false positive and undergoes treatment is not addressed in the risks side. For example, false positive for cancer and the patient needlessly undergoing chemo and/or surgery.
To put it in perspective: A woman when she is highly ( sensitive) she could tell that her son was really Not lying ( ie true negative) about him having finished his broccoli 🥦 ; but if she was not as much specific Her hunch that he was lying ( ie positive ) about finishing the broccoli 🥦.. might not be a correct hunch hence she needs to confirm it by a highly specific by checking the camera footage that she set up earlier while he was supposed to be eating the freaking broccoli 🥦
In medical school and many illustrations and through out my yrs no body bothered to tell me the following : A highly sensitive test will tell you do not have the test and then you should believe it then A highly specific test will tell you do have the disease and then you should believe it Normally, in reality, seNsitive test is followed by a sPecific test to confirm suspicion Take home message N in seNsitive meaning negative result that is credible & P in sPecificity meaning positive result that is credible -- end of the freakin’ story😎
I came here because I needed to sort out the concept of Sensitivity vs Specificity wrt machine learning. This video is perfect for that. The proportion of TP (True positives) classified correctly is sensitivity, the proportion of true negatives classified correctly is specificity. Very succinct, thank you.
Absolute legend!!
You made it crystal clear.. I watched & read many other explanations of this, none was this clear..
Thank you!
You delivered as you promised... I was calculating my sister's APRI score and I found these two terms there... And now I recall that I found these terms on glucometer leaflet and covid rapid test kits and ecocardiogram vs angiography studies.... Thanks
this was one of the best videos on this topic i have seen
Great video! Straight to the point and informative.
Thank you for the video. It was helpful for my purposes. I was a little surprised to see that possible harm to someone who is false positive and undergoes treatment is not addressed in the risks side. For example, false positive for cancer and the patient needlessly undergoing chemo and/or surgery.
VERY HELPFUL!
Finally I understand, thank you!
Thank you so much for making this. Best explanation of the topic ever.
What a perfect explanation!!!
Thanks:)
For the first time, “UNDERSTOOD” . Thanks.......
Great video. Thanks for the easy and simple explanation!
A must watch.Thank you.
So helpful! Thank you! You also win for best hair!
so helpful! thanks
To put it in perspective: A woman when she is highly ( sensitive) she could tell that her son was really Not lying ( ie true negative) about him having finished his broccoli 🥦 ; but if she was not as much specific Her hunch that he was lying ( ie positive ) about finishing the broccoli 🥦.. might not be a correct hunch hence she needs to confirm it by a highly specific by checking the camera footage that she set up earlier while he was supposed to be eating the freaking broccoli 🥦
Helpful.. thanks for sharing
In medical school and many illustrations and through out my yrs no body bothered to tell me the following :
A highly sensitive test will tell you do not have the test and then you should believe it then
A highly specific test will tell you do have the disease and then you should believe it
Normally, in reality, seNsitive test is followed by a sPecific test to confirm suspicion
Take home message N in seNsitive meaning negative result that is credible & P in sPecificity meaning positive result that is credible -- end of the freakin’ story😎
Thank you thank you thank you end of story ! Thank you for your post
Thanks a lot
Wonderful ! So easy to understand and remember .thanks
Too good explanation,you made the concept crystal clear, hope I had you as my teacher in college
Thank you
Stunning stuff!
Great explanation, thanks!
very concise and useful, thanks a lot!
Thank you so much. Very helpful
You are the best
thanks a million
Thanks. Great
nice bro
Ok that still wasn’t easy to understand!
🌷