The tradeoff between sensitivity and specificity

Ebm

[@RaynorsProphet]

You achieved in 12 minutes what my lecturer couldn't achieve in 3 lectures, thank you :)

[@fatimajamil4374]

Same

[@dhiaawad6710]

same here. i had two lectures over that.

[@rgvn5]

3 lectures LMAO mad

[@joecaz]

Best explanation ever! I've looked at multiple descriptions over the last 4 to 5 years, and I was always failed to grasp the concepts completely. I can stop looking for answers now. You have clarified these ideas beautifully. Thank you!

[@andreashimko7464]

Fabulous lecture! Thank you so much! The visuals you learned to explain this did so much more than any 2x2 table I have ever seen.

[@lhsn2881]

Thank you very much, I had taken 3 courses of epidemiology and this the first time I understand very well the tradeoff btw sensitivity and specificity, thank you again. God bless you!

[@nirjhar8353]

Very well done! I sense it clearly now about the importance of the tradeoff! Thanks.

[@studson112]

This was a great explanation - a perfect crash course for review. Thank you!

[@yanyenleungl157]

this binary category is actually so easy to understand. Thank you for explaining it in such a way, Rahul!

[@hollaachagurl92]

Its 2018, and this video is still making an impact!! Thank you so much!!!

[@snekjuce]

@@lekhar5164 2025 now.

[@michellerudolph3425]

Perfectly put! Very clear and concise. Thank you!

[@zahraaammar2708]

this is a truly GREAT and CLEAR explanation !! thank you so much

[@ec3539]

I knew from first few words spoken in your articulate and careful manner that your explanation would be worth listening, and I listened and benefited. Thank you very much. Great teaching skills.

[@falented2]

don't think I will ever forget this again! thanks man.. subbed!

[@biotubeinfo]

Awsome. I finally understand since you do understand what you are talking about. Thanks a lot

[@nachiketgotphode8800]

You have done a great job. Greatful to find you.

[@premminchu]

Thank you so much for this perfectly done video!

[@samisami25]

Thank you Rahul, bliss you May God give you Paradise :-)

[@eddiechapman]

Great job! Very helpful and clear.

[@adorableanish]

2019 and thankful to you. Hope you have a great day!

[@jonahansen]

Best explanation of the medical sensitivity/specificity lingo in terms of the underlying signal detection theory of Green & Swets. I wish they would just use the original labels of hits, misses, correct rejections, and false alarms for the regions, and d' and beta for the test characteristics.

[@rehabalsaleh166]

Absolutely amazing! Thanks a lot!

[@ShinAoki1]

Fantastic video. Thank you.

[@rocketrider1405]

I wish my prof had explained it this way. I really like this.

[@hodigereananda3036]

Rahul , You have made it easy to understand ROC curves. Have followed your videos wheneverI need to understand basics

[@newbie8051]

Great choice of examples !!

[@5rbashat]

That's just awesome!! Thank you so much ✨

[@germangarcia9260]

That was a great explanation. Thank you!

[@CG-rr3wi]

Excellent explanation. Thank you so much!

[@majnooonana]

very good explanation .. I'm specialist and I like how you present this!

[@bevansmith3210]

Brilliant explanation, thank you!

[@gl5183]

What a superb explanation!

[@pamg2628]

Very beautifully explained with great visuals! Thanks Dr. Patwari.

[@natkritalothongdaeng8134]

You safe my life. Thank you sir!

[@43284i]

The phd students in a fancy business school really appreciate you, Rahul. Thank you!

[@boost4O]

Insane video. Thank you so much!

[@anaherrera4805]

Thank you, this helped me a lot! Very good teaching

[@VinceDacer]

Thank you so much for the clear explanation Mr. Rahul!

[@user-jp9zh4gk4l]

Amazing presentation of the content!

Oh... Thank you so much! Why are other people not able to explain it in such a way like you. LOVE YOU ;-)

[@silviachuquichanca7028]

Thanks a lot for the explanation!

[@francocavalla]

Thank you. I am going to use your graphs in a lecture (with proper reference to your video). Great work

[@amir1010010]

Amazing! nice explanation! Thanks.

[@rajdeepbanderjee]

Thank you so much for the video.

[@yazminramos393]

Thanks to your explanation I got it! Blessings Mr Patwari ;)

[@melvingeorge2008]

excellent video... clear voice..must watch video

[@coolbrowser2008]

You explained very neatly. If you have time please put more. Thank you

[@hannahhannahb9650]

excellent presentation. Nice and slow, and very clear

[@VishalSinghVP]

Great video. Just has everything right.

[@ocean694]

Excellent ! Much better than my professor.

[@nurgulsaliyeva8608]

Thank you! So easy to understand!

[@zoyamufti833]

WE NEED MORE TEACHERS LIKE YOU,SUPERB

[@saidasaid9565]

Thank you for your great explanation

[@jihane859]

i finally understand it!, thank you very much!

[@Med.School.Survival]

nice explanation of the trade-off!

[@hoangdaohtd]

Great explanation. Thank you.

[@iloveno3]

Best explanation. Very intuitive.

[@drbniles]

30 fucking years to find this. At last.

[@going_to_the_sky]

Great lecture! Thank you!

[@dhiaawad6710]

man that was so helpful. thank you so much

[@sm11ax]

tussi great ho paaji....thanks for the video

[@stutisinghal1514]

those who teach simply actually know the concept ...u proved u 👏

[@mgoddette1]

So helpful! thanks!

[@jre110872]

OUTSTANDING, RAHUL!!!!!

[@kasonk1692]

GREATE Lecture in just 12 min!!!!

[@DOC7ORT]

Excellent demonstration

[@psychopanda1882]

Amazing explanation Thank youuu:))

[@bishopwashington8640]

so clearly explained!

[@schrodingerssmile9172]

Great stuff!

[@ffidmetham]

amazing explaination that i am looking for

[@amethyst4444]

AMAZING VIDEO!!! THANK YOU SO MUCH!!!

[@KaennC]

While almost any online lesson/lecture made by indian people is top notch, it's often buried under thick illegible accent. Your voice is crisp and you've found an efficient way to explain this. Thank you.

[@ethanmaxwell2235]

ironic that you typed illegible while meaning unintelligible in a comment critiquing others' use of the English language

[@dhisney]

BLESS YOU, OH KIND SIR! MAY YOU ALWAYS BE UNDER GOD'S PROTECTION!

[@sheilahernandez5318]

Thank you soooo much!

[@boezzat]

what the hell is this AWESOME lecture ! thanx

[@tsrevo1]

Excellent. really really excellent.

[@GuruprakashAcademy]

WOW GREAT EXPLANATION

[@eyeofthetiger0030]

thanks dude, good work!

[@raghadpnu6221]

this is so helpful thank you so much!!!!

[@asheikh2561]

thank u for making my life so easy

[@bonitamathew1141]

this is brilliant thank you

[@taraaziz2199]

So useful! thank u!

[@priyabratamallick5073]

Great explanation

[@CreationGames123]

Great explanation.

[@phuccoiinkorea3341]

You rock!

[@TylerdurdenFc1997]

You are a legend

[@nehapruthimds]

thank you !wonderful explanation.can I please ask how do we decide a cut off/ classification algorithm for a given dataset ?

[@bonsonsm]

Thank you...!

[@ericnyirenda9582]

THANK YOU!!!

[@tiffanymanangatheawesome950]

Thank you 😀

[@fatimamohammad1439]

Thank uuuu great job

[@HugueteBastida]

very nice video!! thank you

[@narayanmritunjay1013]

great, thanks

[@vwziful]

wow! bravo .I dont think there is any room for improvement .I hope , hope hope you have more videos on screening tests and biases as well.Lets see .

[@fatboy117]

amazing Thank you.... better lecture than Kaplan Biostats

[@156abdu]

Brilliant

[@junxikang1583]

cheers!

[@aaaa-sq6xp]

awesome

[@anfaljar5062]

?? thank you , but I want to know if I put the threshold in the middle of overlap so the sens will equal the spec

[@JK-lh9yq]

Thanx alot

[@nnp418]

Hi, I am confused about the cutoff point for most of the true positives, the highest positive predictive value, the lowest negative predictive value and the highest specificity on graph. At what point, I get most of the true positives and at what point I get the highest specificity. I hope someone clarifies these. I would be much more appreciated.

[@melissacowgillhs]

Thank you very much for the video... but what about Positive predictive value and negative predictive value variations?

[@oldblueday]

Those depend on the prevalence of disease, which isn't really depicted in these histograms. I did go over that in this video, though: EBM: predictive values