Intense Analytics

Object detection has come a long way, and the YOLO (You Only Look Once) series has been a key contributor to its progress. The latest in this line, YOLOv8, offers a powerful, flexible, and easy-to-train framework for both detection and segmentation. In this post, we will walk through how to train YOLOv8 on your own custom dataset. What Is YOLOv8? YOLOv8 is an object detection model developed by Ultralytics. Unlike previous versions, YOLOv8 supports not only detection, but also classification and segmentation tasks out of the box. It is optimized for speed and accuracy, and it comes with a modern Python-based interface. Step 1: Install YOLOv8 First, install the Ultralytics package using pip: pip install ultralytics This gives you access to the `yolo` CLI and Python A...

Overview The market for Personally Identifiable Information (PII) redaction tools is increasingly saturated with AI-powered solutions. However, for highly sensitive healthcare datasets, traditional deterministic techniques—especially dictionary- and pattern-based methods—offer a safer and more controlled approach. This document outlines the rationale behind favoring deterministic methods and explains the strengths and limitations of each. Context: The Risks of Handling PII Healthcare datasets often include sensitive personal details such as: Patient names, dates of birth, addresses, phone numbers, and emails Medical record numbers and Social Security numbers Insurance information, policy numbers, and group IDs Diagnoses, medications, dosages, treatment plans, and lab results Provider names and contact information Given the high stakes involved, it is critical to err on the side of caution —over-redacting when in doubt. The risk of exposing sensitiv...