Python

Introduction to Python programming for medical data analysis, covering essential libraries like NumPy, Pandas, and scikit-learn with practical examples for healthcare applications and clinical research.

Create a Medical Database with Docker: Complete Guide with SQLAlchemy, and Flask

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Introduction: Why Build a Medical Database with Docker? Creating a robust medical database system requires careful consideration of security, scalability, and maintainability. Furthermore, Docker containerization offers an ideal solution for healthcare applications by providing isolated environments that ensure consistent deployment across different systems. In this comprehensive tutorial, we’ll explore how to create a medical database … Read more

UNet

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Introduction UNet is a convolutional neural network (CNN) introduced by Olaf Ronneberger in 2015. These specialized neural networks learn to recognize objects in images. When properly trained, they can analyze medical images, detect specific features (such as neoplasms in CT scans), and classify different types of images (such as distinguishing between pneumonia and neoplasms). In … Read more

Sensitivity Analysis

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Definition Sensitivity analysis is a collection of techniques that determine how input parameters affect model results. Specifically, it measures how much variation in the results stems from different types of uncertainty. For a model: $Y=f(X_1,X_2,X_3…..X_n)$ examines how Y changes when each X is modified. Sensitivity analysis can be applied across several key areas: predictive models, … Read more

Random Numbers in Python

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Why do we need random number generation in statistics and data science? Data scientists and statisticians rely on random number generation for several important purposes. They can be used to create data samples, which serves as a foundation for advanced statistical techniques. This includes Bootstrapping methods that involve resampling from existing data to create new … Read more

Programming Paradigms in Python

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A programming paradigm is the model or approach used to logically organize a program. It defines how different parts of a program interact and work together. A programming paradigm encompasses three key aspects: Paradigms Let’s explore the main types of programming paradigms Imperative Paradigm This paradigm involves giving the computer explicit, step-by-step instructions using variables, … Read more

Visualizing Statistical Distributions with Python

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This post illustrates techniques for visualizing statistical distributions using Python and its graphics libraries, particularly Matplotlib. The resulting charts are used in the statistical distributions lesson of the statistics course. Required Libraries Import Normal distribution Exponential distribution Bernoulli distribution Binomial distribution Poisson distribution Uniform distribution Chi square distribution t distribution vs normal distribution Sigmoid function

Inside Dicom

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In a previous blog post, we explored how to read the content of a DICOM file, including its numerous tags. These tags provide insights into the study type, characteristics, and all relevant patient and study information. Now, we’ll focus on the most crucial tag—the one containing the images. A typical study can include anywhere from … Read more

Matplotlib (2)

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Following our general introduction to the matplotlib environment, let’s explore the types of graphs this Python library can produce. Among the most commonly used graphs for data presentation are: Histograms Histograms primarily illustrate the distribution of a continuous variable. The data is divided into uniform intervals (bins), and the frequency of each bin is represented. … Read more

Matplotlib (1)

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Python offers several libraries for creating professional graphs, but Matplotlib stands out as the foundation upon which many others are built. Often referred to by its alias “plt,” Matplotlib enables users to generate complex, element-rich graphs as well as multiple visualizations. Another popular library, Seaborn (alias “sns”), functions as an extension of Matplotlib and requires … Read more

Character Encoding

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Character encoding is the process of assigning a unique number to each character, enabling computers to exchange data in a standardized and unambiguous manner. Various encoding systems have developed over time and across different regions. These systems often lack compatibility, have space limitations (and consequently character limitations), and may use the same encoding for different … Read more