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.
Deleting the patient name from a DICOM file feels like anonymization. It is not. A cardiac CT study I once pulled for a teaching file had a blank PatientName, a scrubbed PatientID, and a perfectly readable date of birth sitting three tags down in a private block the vendor never documented. The header looked clean. … Read more
Non-inferiority Trials in Medicine: Last updated: June 2026 Author: Michele D. Pierri Reading time: 15–20 minutes In clinical research, we are used to thinking that a new drug, device, or procedure should be tested by asking a simple question: Is it better than what we already have? This is the logic of a superiority trial. … Read more
Machine Learning and Large Language Models for Clinical Text Analysis Article authored by Michele D. Pierri, MD Cardiac Surgeon & Medical Technology Researcher Last updated: May 2025 Reading time: 30 minutes Abstract The first two articles in this series traced a progression from rule-based pattern matching (regular expressions) to linguistic analysis (spaCy/scispaCy) for extracting structured … Read more
Non-Parametric Statistics in Medicine: A Practical Guide for Skewed, Ordinal, and Small Clinical Datasets Last updated: May 2026 Author: Michele D. Pierri Reading time: 15–20 minutes Introduction Clinical data rarely behave like the textbook examples we encounter in introductory statistics courses. Length of stay tends to be right-skewed. Biomarkers such as C-reactive protein, ferritin, D-dimer, … Read more
Introduction to Natural Language Processing for Medical Report Analysis: Advanced Linguistic Analysis with spaCy and scispaCy for Medical Reports Article authored by Michele D. Pierri, MD Cardiac Surgeon & Medical Technology Researcher Last updated: May 2025 Reading time: 30 minutes Abstract Regular expressions give us a solid foundation for pulling structured data out of clinical … Read more
Introduction to Natural Language Processing for Medical Report Analysis: Pattern Matching with Regular Expressions Article authored by Michele D. Pierri, MD Cardiac Surgeon & Medical Technology Researcher Last updated: January 2025 Reading time: 25 minutes Abstract Medical discharge summaries contain critical clinical information that remains largely inaccessible to automated analysis due to their unstructured nature. … Read more
Introduction The softmax function is essential in mathematics and machine learning. It transforms a vector of real numbers into a probability distribution. Put simply, it converts a set of numbers into probabilities. To understand how it works, let’s look at a list of risk values for some patients: Patients Surgical Risk Patient A 2 Patient … Read more
Introduction Decision Curve Analysis (DCA) is a powerful tool for evaluating the clinical utility of predictive models and diagnostic tests. Unlike traditional metrics like AUC or calibration, DCA focuses on what truly matters in practice: whether using a model leads to better decisions and outcomes. DCA was introduced by Vickers and Elkin in 2006 to … Read more
Understanding DICOM Coordinate Systems and Image Orientation: Why Your 3D Volume Looks Upside Down 1. Introduction — Why Orientation Matters Have you ever opened a medical image and found the anatomy upside down or mirrored? It’s not your viewer’s fault — it’s about geometry. DICOM files contain not only pixels, but also the mathematical information … Read more
A technical comparison between TCP and UDP protocols implemented in Python: examining performance metrics, security considerations, and practical applications within healthcare systems using FHIR standards for effective data exchange between medical platforms. Introduction: The Significance of TCP vs UDP When browsing websites, streaming videos, or making video calls, our data travels across networks using protocols … Read more