BC HEALTH
Saved by @jay_millerjay

You gotta think about this one carefully!

Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)

The test is 99% effective in detecting both sick and healthy people.

Your test comes back positive.

Are you really sick? Explain below 👇

 The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through it!

https://t.co/jGt006Vlh5
You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.

👇
Here is what we know:

- Out of 10,000 people, 1 is sick
- Out of 100 sick people, 99 test positive
- Out of 100 healthy people, 99 test negative

Assuming 1 million people take the test (including you):

- 100 of them are sick
- 999,900 of them are healthy

👇
Let's now test both groups, starting with the 100 people sick:

▫️ 99 of them will be diagnosed (correctly) as sick (99%)

▫️ 1 of them is going to be diagnosed (incorrectly) as healthy (1%)

👇
Let's now test the group of 999,900 healthy individuals:

▫️ 989,901 of them will be diagnosed (correctly) as healthy (99%)

▫️ 9,999 of them will be diagnosed (incorrectly) as sick (1%)

👇
Since your test came back positive, it means that you belong to either one of the groups that had a positive result:

1. 99 people that are truly sick, or
2. 9,999 people that are actually healthy (but were diagnosed as sick.)

👇
Basically, out of 10,098, only 99 are truly sick.

That'll give you a 0.98% chance of being sick!

So no, most likely, you are fine!

👇
Here is something important: this is true as long as our only priors are that 1 in 10,000 people have the disease.

For example, if you were showing symptoms, then your chance of being sick after receiving a positive test will be higher.

More from Santiago

Santiago
Santiago
@svpino
Machine learning education is broken.

If you are preparing for a research position, you are good. If you are looking to get out there and start solving problems, not even close.

Here are some thoughts so you can get ahead.

↓

Most classes, courses, and books cover the same road.

They start with a dataset. They finish with a working model. The focus is always on everything that happens in between.

Dataset → Model.

This is great, but not enough.

Real-life situations rarely start with a dataset, and they never end after you finish building your model.

Applying machine learning successfully is hard.

Here are a few examples that you should keep in mind.

First challenge: Properly framing up the problem.

If you don't understand the problem, you can't determine what data you need. If you don't understand the data, you can't build a good model.

I've never seen a company that had their data ready to go.

In fact, most of them don't even have data at all and need you to determine what exactly they should start collecting.

You usually have to go Problem → Potential Solution → Data.
ALL
Santiago
Santiago
@svpino
11 key concepts of Machine Learning.

— Supervised Learning Edition —

🧵👇

😜

Before starting, remember that, if you follow me, one of your enemies will be immediately destroyed (and you'll get to read more of these threads, of course.)

And if you don't follow me, well, you just hurt my feelings.

😜

1. Labels

(Also referred to as "y")

The label is the piece of information that we are predicting.

For example:

- the animal that's shown in a picture
- the price of a house
- whether a message is spam or not

👇

2. Features

(Also referred to as "x")

These are the input variables to our problem. We use these features to predict the "label."

For example:

- pixels of a picture
- number of bedrooms of a house
- square footage of a house

👇

3. Samples

(This is also known as "examples.")

A sample is a particular instance of data (features or "x.") It could be "labeled" or "unlabeled."

👇
MACHINE LEARNING
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Santiago
Santiago
@svpino
11 short programming problems to stretch your imagination and make sure you are staying on your toes.

(Starting with the simple ones, they get more fun as you move towards the end.)

🧵👇

1. Write a function that reverses an array in place.

In other words, the function should not use an auxiliary array to do the work.

2. Write a function that finds the missing number in an unsorted array containing every one of the other 99 numbers ranging from 1 to 100.

3. Write a function that finds the duplicate number in an unsorted array containing every number from 1 to 100.

Only one of the numbers will appear twice.

4. Write a function that removes every duplicate value in an array.

There could be more than one value duplicated. You should remove all of them leaving a single copy of the value.
TECH
Santiago
Santiago
@svpino
The two main machine learning techniques used in the industry today:

1. Gradient Boosted Trees
2. Deep Learning

Focus your time learning Scikit-Learn, XGBoost, and a Deep Learning library like Keras or PyTorch and you'll get the most for your time.

If you need to deal with structured data: Scikit-Learn + XGBoost.

If you need to deal with unstructured data (perceptual tasks): Keras or PyTorch.

Of course, there are many more techniques that will be helpful, but if you focus on these you'll be maximizing your ability to deliver value in the short term.
DS
Santiago
Santiago
@svpino
What's machine learning?

Not a framework. Not a different language. Not the latest "cool" thing around the Internet.

Thread: Let me convince you that machine learning is the best thing since sliced bread 🍞.

Let's start with a simple exercise:

"Write a function that returns 0 if a supplied number is even or 1 if the number is odd."

If you are a developer, I'm sure you know how to write this function. It should be simple, right?

To avoid using a specific syntax, let's represent this function as follows:

y = f(X)

Where:
• X → The input number
• y → The result (0 if even, 1 otherwise)
• f → The function that does the work

We can now get to the interesting part.

If you are a programmer, writing this function is simple.

You know the relationship between X (the input number) and y (the output), so you can easily write the rules (the function.)

In machine learning, we don't write the rules. We learn them.

Imagine we had an algorithm that processes many samples (X → y), learns the relationship between them, and comes up with the correct rules.

We call these samples "training data," and they would like like this:

• 2 → 0
• 5 → 1
• 8 → 0
• 4 → 0
• 3 → 1
• ...
ALL

More from Health

Plum
Plum
@getplumhq
12 things you should look out for before buying health insurance

A thread 🧵

It’s a good idea to make sure your health is protected under an insurance policy so that you don’t shell out large sums of money for hospitalization and treatment. But buying an individual health insurance policy can be daunting in itself.

Websites and policy documents can be overwhelming. There’s a lot of loaded terms, there’s a whole bunch of things that your policy may or may not cover. It’s important to know and understand the details though, so you’re not surprised later.

In this thread, we'll talk about the things you absolutely need to watch out for when buying an individual health insurance policy for yourself or your family members :)

If you take an individual health insurance policy and the insurance company offers to pay up to ₹15 lakhs during the year whenever you’re diagnosed with a disease or meet an accident, that amount is the 'sum insured'.
HEALTH
Enigma
Enigma
@ainittomai
On December 29 we were dillucidating here if the drops meant "surprise, relatively neutral expression" or "a negative expression, horror" (Remember: https://t.co/J2gjQjAENw ). Well, December 22 drops seem to clarify it. First, the December 29 drop that generated the confusion 1/*


didn't appear in today drops, while several old ones have been posted again. I would say that all December 22 drops regarding facial expression mean and clarify "surprise". 2/*


More 3/*


And more. So, they didn't point to a negative event, just to one that generates surprise. 4/*


All these drops were completed with a Christmas gift one, confirming the surprise neutral meaning and adding a related positive one connected to the surprise. 5/*
HEALTH
Advertisement
Ottawa Public Health
Ottawa Public Health
@OttawaHealth
THIS IS A CATCHY & ATTENTION-GRABBING TITLE

Today, the Province will likely announce what zone of the reopening framework we'll shift into as of Tuesday. Whatever is announced, though, doesn't change what we need to do. Why?

Kindly read these 14 tweets & we'll tell you. (1/14)

Fun fact: COVID-19 does not follow us on Twitter. COVID doesn't know, or particularly care, if we're in the Red or Orange zone.

The behaviours of the virus do not depend on the current ‘zone’ of public health restrictions. And, to be perfectly candid, neither should ours. (2/14)

Once upon a time we used to say #WeAreInThisTogether in our messaging. Here's the thing: we are, but we aren't. Not everyone is experiencing this pandemic the same.

Nurses, doctors, paramedics & healthcare workers have experienced things much differently than most of us. (3/14)

Some people have been home & isolated for months, while others haven't been able to stop working.

Business owners & hospitality workers have been on a rollercoaster of openings & closures.

Students, parents, teachers & school staff have had to adapt to going from online (4/14)

to in-person learning (and back again) numerous times.
And this virus has disproportionately affected some groups more than others.

But there's the thing: while our experiences of this pandemic haven't been shared, we do have a shared goal.

And we can reach it together. (5/14)
HEALTH
Starks\u262a\ufe0f\U0001f1f9\U0001f1e9
Starks☪️🇹🇩...
@MegaIntelIect
Thread on how atheism leads to mental retardation (backed with medical citations🧵💉)

To start with, atheism is an unnatural self-contradicting doctrine.

Medical terminology proves that human beings are naturally pre-disposed to believe in God. Oxford scientists assert that people are "born believers".

https://t.co/kE0Fi588yn
https://t.co/OqyXcGIMJn


It should be known that atheism could never produce an intelligently-functioning society and neither ever will.

Contrastingly, Islam produced several intellectuals & polymaths, was on the forefront of scientific development, boasting 100% literacy


It is also scientifically proven that atheism led to lesser scientific curiosity and scientific frauds, which is also why atheists incline to pseudo-science.

Whereas, religion in general and Islam in particular boosted education.

https://t.co/19Onc84u3g


Atheists are also likely to affected by pervasive mental and developmental disorders like high-functioning autism.

Cognitive Scientists and renowned Neurologists found that more atheism is leads to greater autism.

https://t.co/zRjEyFoX3P
HEALTH
Dr Chioma Nwakanma
Dr Chioma Nwakanma
@DrZobo
@SMILEWithmeNGO Hello @SMILEWithmeNGO I am glad to be here. Thank you for having me.

A very big welcome to everyone joining today’s conversation. Our guest today needs no introduction especially in the sphere of cancer control and advocacy. Welcome @runciecwc
#CheatCervicalCancer


@runciecwc Q1: So Runcie @runciecwc, we see all the amazing work you do as an advocate.
Can you share with us some of the work that you have been doing in cancer control in Nigeria?
#CheatCervicalCancer

@runciecwc That’s amazing. Your work speaks for you. Thanks for all you do.
Q2: What is this @WHO Global Strategy to accelerate the Elimination of CervicalCancer? Can you elaborate on it?
#CheatCervicalCancer

@runciecwc @WHO Q3: In your experience, so far what are the greatest challenges you have identified with cancer control in Nigeria?
#CheatCervicalCancer.

@runciecwc @WHO Q4: Interestingly, we have seen that your organization is part of the Coalition of CSOs against Cervical Cancer in Nigeria, @CervicalCancerN, what is the goal of this Coalition? #CheatCervicalCancer
HEALTH

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Many readers have asked me "why do so many pulp covers feature women in ripped red blouses standing in swamps while a man fights off an unusual animal attack?"

The answer is artist Will Hulsey...


Will Hulsey was the undisputed king of the animal attack pulp cover. You name it, he'd paint it attacking you in a pool of stagnant water.


Very little is known about Will Hulsey, but he worked on a number of men's pulp magazines in the 1950s and early 1960s including Man's Life, True Men, Guilty, Trapped and Peril.


Their audience was ex-GIs: during WWII the US Council of Books in Wartime had given away over 122 million books to American servicemen to read; this led to a post-war surge in paperback and magazine sales amongst these newly enthusiastic readers.


As a result the 1950s saw a raft of men's pulp magazines being published to tap into this market - almost 200 different titles!
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Butt plugs were originally sold as a miracle cure for headaches, acne, and insanity

Thread, article here and h/t: @qikipedia :
https://t.co/Ts84xnmWKJ


For a long time, medicine was pre-occupied with the question "can this be solved by putting something in the butt?"

Take, for example, tobacco smoke enemas, in which 18th Century physicians saw drowning victims and attempted to de-deadify them by blowing tobacco smoke up their rectums with a pipe.


Despite having no medical benefit whatsoever, the practice was popular, and enema kits lined the Thames like lifebelts, ready to be used as one final humiliation for somebody who was crap at swimming.

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Billy Bostickson \U0001f3f4\U0001f441&\U0001f441 \U0001f193
Billy Bostickson 🏴👁&👁 ...
@BillyBostickson
Enough Jaw Jaw, this is War!
1. People's Justice Courts to be set up worldwide
2. Citizens' arrests of all Identified Suspects
3. Lab Inspections
3. Harsh interrogation using MKULTRA
4. Public Show Trials video streamed live
5. Cross Questioning of suspects via Twitter & Zoom
6.


A growing list of suspects to be interrogated


Foul Traitors, Charlatans, Frauds, Bat Molesters! Frankensteins, Well Poisoners, Plotters, Deceivers!
Dr. Shipmans, Saboteurs, Devils in White Coats!


Organisations to be Investigated
WIV
Wuhan University IMA
WIBP
WCDC
BEIJING IPB
Nanjing Military Lab
SinoPharm
BARDA
NIH
EMERGENT BIOSOLUTIONS
BIOPORT
GILEAD
SIAC
QTEL
USAMRIID
FORT DETRICK
DARPA
DTRA
Metbiota
ONE HEALTH
GVP
ECOHEALTH
MITRE
BATTELLE
TUNNELL
LAURIMA GOV SERVICES


Suspects (1)
China
Zhengli Shi
Peng Zhou
George Gao
Deyin Guo
Major General Chen Wei
United States
ALEX AZAR
JONNA MAZET
ALISON O’TOOLE
ANTHONY FAUCI
BOYD YOUNT
DAVID FRANZ
DAVID KARESH
DENNIS CARROLL
DYLAN GEORGE
GEORGE PAINTER
IAN LIPKIN
JENS KUHN
JEROME HAUER
JONATHAN EPSTEIN
WORLD , ALL
Anu Satheesh \U0001f1ee\U0001f1f3
Anu Satheesh 🇮🇳...
@AnuSatheesh5
#Guruvayur_Krishna_Bhakthi  🕉
#Guruvayur
#Storytime
Beautiful Story of Guruvayurappan

Poonathanam Namboothiri was a great devotee of Guruvayurappan. One day Poonthanam was going to Guruvayur Kshetram. It was night time and eventhough Namboothiri was tired he continued to walk


Suddenly some thieves came and blocked his way. Poonthanam cried for Shri Krishna to help. Thieves snatched all valuables from him, but Namboothiri holding his Bhaghavatam book called Shri Krishna to help. That time a man came in a horse back and fought with thieves and protected


Namboothiri. Poonthanam thanked Krishna for helping him from danger and said to the man that "Shri Krishna has send you here and I don't know how to thank you".  The man smiled and told that he is Mangattachan, minister of  samoodhiris. Poonthanam once again thanked him and


gave his ring to Mangattachan as a token of thanks and continued his journey. He reached Guruvayur early morning for Nirmalya Darshan. Temple poojari came near him and told that Guruvayurappan came in his dreams and asked to hand over the ring to poonthanam.


When he opened Kshetra Nada poonthanam was surprised to see his ring on Guruvayurappan, which he gifted to Mangattachan. He understood that it was Guruvayurappan who came as Mangattachan to protect him. This is how Bhagwan treat his devotees.

Hare Krishna
🙏🕉🙏
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Anu Satheesh \U0001f1ee\U0001f1f3
Anu Satheesh 🇮🇳...
@AnuSatheesh5
Chennimalai Murugan Kovil
#Erode
#TamilNaduTemples 🚩

Chennimalai Murugan Temple is located  near Perunthurai in Erode District. Murugan is worshipped here as Dandayudapani. Temple is situated on the banks of Noyyal river also called Kanchima Nadhi. Temple is situated in a hill


Sthala Puranam says that, there lived a Landlord who had many cows in his farm. One among them was a Black Cow, which didn't give milk. Land lord observed that evening time, when all the cows came back after grazing, this cow used to go to a particular spot and gave all  the milk


by itself. He decided to dig the spot where the cow gave its milk

On digging a beautiful Vigraham of Murugan was found, but lower portion was very rough. So he called a great sculptor to soften it. Everyone was shocked to see that on the first chisel the vigraham bleeded.


Land lord realized that Murugan wanted the Vigraham the way it was.

Thus Prathishta was done on Chennimalai hill. It is believed that Sivalaya Chola got relieved from his Brahmahatti Dosha here. Kanda Shasti Kavacham was first offered here.

Muruganukku Haro Hara
🙏🕉🙏
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