Prostate Cancer: the Difficult Path to a Correct Diagnosis

Prostate cancer (PCa) is one of most frequent malignancies in men worldwide. For example, about 190,000 new cases of prostate cancer are diagnosed in the United States annually. In addition, PCa is the second leading cause of cancer death in men. For this reason, it is crucial to accurately diagnose this disease.

The fundamental premise of the PCa diagnosis is the pathomorphological study of biopsy samples of prostate tissues and cells or postoperative materials. A pathologist can determine not only the presence and type of tumor, but also the growth and aggressiveness of malignancy and the disease prognosis. This information helps choose the optimum treatment for each patient — surgery, radiation therapy, or active monitoring.

#ai #pathology #diagnostic #neural-networks #prostate-cancer

What is GEEK

Buddha Community

Prostate Cancer: the Difficult Path to a Correct Diagnosis

Prostate cancer (PCa) is one of most frequent malignancies in men worldwide. For example, about 190,000 new cases of prostate cancer are diagnosed in the United States annually. In addition, PCa is the second leading cause of cancer death in men. For this reason, it is crucial to accurately diagnose this disease.

The fundamental premise of the PCa diagnosis is the pathomorphological study of biopsy samples of prostate tissues and cells or postoperative materials. A pathologist can determine not only the presence and type of tumor, but also the growth and aggressiveness of malignancy and the disease prognosis. This information helps choose the optimum treatment for each patient — surgery, radiation therapy, or active monitoring.

#ai #pathology #diagnostic #neural-networks #prostate-cancer

Correct Your Sitting Posture - How to Sit at Your Desk

Learn on correct your sitting posture or how to improve your posture so that you can not only correct your bad posture but also help your back stay healthy.

#how #correct your sitting posture #how to sit at your desk correctly #how to sit at your desk correctly

So You've Fucked up your Python Path

I remember back to when I first learned Python. It was a strange decision for a happily employed post-graduate to make, especially for a time when many were screaming for the death of the language with Guido’s (outrageous?) grand reveal of Python 3. The Ruby on Rails guys seemed to be doing just fine. Those were the days.

After weeks of sweating over a keyboard in the basement of an illegal Bedstuy hostel, I had finally set out what I had hoped to achieve. It was the greatest credential any programmer could possibly strive for: yes ladies and gentlemen, none other than yours truly became an officially recognized licensed professional: I had just completed the last Python course in Codecademy.

Congratulations, you know nothing

Armed with this new unfathomable knowledge, I was ready to take on the world. I did have a few gaps in my knowledge, such as:

• Experience with Linux
• General idea of what a terminal is and why anybody would use one
• Basic understanding of the internet
• Motor skills needed to survive

That aside, I was determined. Nothing could stop me, which turns out to be a really bad attitude when you’re SSHed into a VPS with root access, and zero hesitation to wreak havoc upon any and all system files. You see where this is going.

#python #devops #python path #fucked #path

Personalized Cancer Diagnosis

“Once sequenced, a cancer tumor can have thousands of genetic mutations. But the challenge is distinguishing the mutations that contribute to tumor growth (drivers) from the neutral mutations (passengers).

Currently this interpretation of genetic mutations is being done manually. This is a very time-consuming task where a clinical pathologist has to manually review and classify every single genetic mutation based on evidence from text-based clinical literature.We need your help to develop a Machine Learning algorithm that, using this knowledge base as a baseline, automatically classifies genetic variations.”

~~Kaggle

_For implementation please follow the link : _https://github.com/vedanshsharma/Personalized-Cancer-Diagnosis

Introduction

The task of identifying the type of variation of the gene is typically a three step process. Our task is to use a model to automate the third step which is the most time consuming step for a molecular pathologist. This involves analyzing the evidence related to each of the variations to classify them. More formally our problem statement is -

Classify the given genetic variations/mutations based on evidence from text-based clinical literature.

Source: https://www.kaggle.com/c/msk-redefining-cancer-treatment/discussion/35336#198462

Business objectives and constraints.

• No low-latency requirement. Since we don`t have a strict latency requirement we can train complex models as long as we our model is taking reasonable amount of time.
• **Interpretability is important. **A doctor might want to cross check the results and for this he might require the algorithm to explain itself. For this interpretability should be high.
• **Errors can be very costly. **Since this is a matter of life and death , we need a model with high accuracy.
• Probability of a data-point belonging to each class is needed. This will let the doctor decide at the end to which class the variation belongs to. In case of equiprobable classes, the doctor will be able to decide by performing tests, rather than the model returning a single class.

---

Machine Learning Problem Formulation

Data

• We have two data files: one contains the information about the genetic mutations and the other contains the clinical evidence (text) that human experts/pathologists use to classify the genetic mutations.
• Both these data files are have a common column called ID
• Data file’s information:

1. training_variants (ID , Gene, Variations, Class)
2. training_text (ID, Text)

Mapping the real-world problem to an ML problem

There are nine different classes a genetic variation/mutation can be classified into. This implies that our problem is a **multi class classification **problem. The performance metrics that we will be using are -

• Multi class log-loss, Since we want to output probabilities that a given variable x_i belong to classes 1–9.
• Confusion matrix

So our final objective is-

Objective: Predict the probability of each data-point belonging to each of the nine classes.

And our final constraints are-

• Interpretability ,models like naive bayes , linear svm or DTs can be trained as they have high interpretability. We should probably avoid using models like RBF svm.
• Class probabilities are needed.
• Penalize the errors in class probabilites => Metric is Log-loss.
• No Latency constraints.

Train, CV and Test Datasets

Our data is not temporal in nature i.e. it doesn`t change with time. Hence we will be randomly splitting our data set into train Cv and test set with sizes being 64% (80 % of 80), 16 %(20% of 80) and 20% respectively.We will split the data in such a way that the distribution of class label remain conserved.

---

Exploratory Data Analysis

Text Preprocessing

We will be doing some basic text preprocessing which includes-

• Removing stop words.
• replacing every special character with space.
• replacing multiple spaces with single space.
• converting all the chars into lower-case.

There are few null values present in text.

#cancer #machine-learning #random-forest #data analysis

FaucetCryptoBot | A Bot for FaucetCrypto a Cryptocurrency Faucet

A bot for the high paying popular cryptocurrency faucet Faucet Crypto. The bot is built using Python and Selenium, currently it is under active development and, can do tasks like PTC ads, main rewards, and shortlinks except exe.io and fc.lc

Status

Seems like Faucet Crypto has started using a bot detection system so you may need to obfuscate your driver to prevent it's detection. Please see below for the detailed instructions.

The xpaths have been updated and new xpaths have been written to xpath.py you can replace the new file with the old file. Since i had to rush throught this if i missed something please let me know

The layout of Faucet Crypto has changed and the bot won't work anymore you can wait for me to release the updated xpath file or you can add them manually to the xpath.py file.

The issue of the bot was unable to find the claim button was fixed. The reason was due to an update in Faucet Crypto website. New xpaths have been updated you can copy the new xpaths to your old xpaths file. (keep and eye on the bot status for further changes and updates that might occur.)

Disclaimer

Please be note that this is the first major automation project for me. I am by no means responsible for any usage of this tool, Account bans or Nuclear winter. Use it on your own behalf. I'm also not responsible if your account get's banned.Therefore, if the Faucet Crypto devs catches you and get you banned,then don't point your fingers at me, for getting your account deleted? I will rolling on the floor laughing at you.

Faucet Crypto

If you found this repo useful please don't forget to give me a ⭐

Brave Browser

The browser of choice for this project is Brave browser due to its native ad-blocking scripts which are pretty good and prevents random popup openings, which can mess with the bots proper execution.

If you don't have Brave browser installed you can download it from here.

Changes

v2.98

• Added much better error codes
• If the bot is run in headless mode it wont load images imporving load times significantly
• Instructions for driver obfuscations have been provided
• Much efficent compared to the previous versions
• Achievements collector has also been added but its only experimental and is disabled by default in the bot.py file you can use this feature by uncommenting it
• Also added a feature where the bot screenshots the stupid popup ads that creep in from time to time.
• If the bot detects that the captcha is being triggered it will sleep for an hour before executing again.
• Fake User Agent has been added
• Option for completing fc.lc shortlinks added but disabled by default, cause it dosen't work always you can test it out by uncommenting the sections below it in FaucetCryptoBot/fcbot.py.
• Bot automatically closes the modal and chat which was an issue in the previous version.
• Resolved the issue where the watch button for sh.faucetcrypot.com was covered by the chat button and throwed an error.
• Removed the annoying 'NoneType' object has no attribute 'text' errors.
• Replaced pickle5 with pickle-mixin cause pickle5 was causing issues for windows users.
• Changes in requirements.txt file

v2.88

Added logic to save cookies and use them for logging in. This prevents using the default profile directory of your browser and dosen't mess it up.

Added logic to close the welcome modal and chat which covered the dashboard visibilty.

Cookies are now saved to a cookie file if it is not present in the directory the bot will automatically login with the user email and password provided on the config file and generate a new cookie file.

Added proxy incase you want to generate some referrals. This method is not recommended yet and try this at your own risk.

Fixed the issue when the browser was running in normal mode the bot closing all the open tabs.

Installation

create a virtual environment with virtualenv

virtualenv env

Activate the virtual environment

source env/bin/activate

Install all the necessary packages

pip install -r requirements.txt

Important

The following is important to better hide your chromedriver

Replacing cdc_ string

You can use vim or perl to replace the cdc_ string in chromedriver. Using vim or perl prevents you from having to recompile source code or use a hex-editor.

Make sure to make a copy of the original chromedriver before attempting to edit it.

Our goal is to alter the cdc_ string, which looks something like $cdc_lasutopfhvcZLmcfl.

Using Vim

vim /path/to/chromedriver

After running the line above, you'll probably see a bunch of gibberish. Do the following:

Replace all instances of cdc_ with dog_ by typing :%s/cdc_/dog_/g. dog_ is just an example. You can choose anything as long as it has the same amount of characters as the search string (e.g., cdc_), otherwise the chromedriver will fail.

To save the changes and quit, type :wq! and press return. If you need to quit without saving changes, type :q! and press return.

Using Pearl

• The line below replaces all cdc_ occurrences with dog_.

perl -pi -e 's/cdc_/dog_/g' /path/to/chromedriver

• Make sure that the replacement string (e.g., dog_) has the same number of characters as the search string (e.g., cdc_), otherwise the chromedriver will fail.

Setup

Set the correct path for your brave browser in the config file config.py

[Browser]
browser-mode =              #takes two parameters headless or leave it empty
driver-path =               #path to your chrome driver
browser-binary-location =   #path to your browser binary location

[User]
mail =                      #Your faucet crypto account mail
password =                  #your faucet crypto account password

[Misc]
debug =                     #takes two arguments True of False
proxy =                     #proxy address and port try not to use a proxy
                            #and leave this empty

Run

Run the bot by

python bot.py

Account setup

If it's your first time running the bot you need to login to Faucet crypto. Run the bot in normal-mode(default) it will redirect to login page where you can login, the bot will do the rest from there by collecting from all the ads. (Note) The bot can't yet do the exe.io and fc.lc shortlinks so you would have to help it do that. If you've logged in successfully then you can run the bot in headless mode from then on you can set the bot to headless mode by setting the "headless" flag in the config file.

browser-mode = "headless"

Contributions

Feel free to contribute to this project and help me improve this project

Thank You,

Download Details:
 

Author: souravrs999

Download The Source Code : https://github.com/souravrs999/FaucetCryptoBot/archive/refs/heads/main.zip 

GITHUB: https://github.com/souravrs999/FaucetCryptoBot