datdigitaladdict/healthconnect-experience-lab

AnalystLab Africa Experience Lab - HealthConnect Clinic: reducing patient no-shows using data and AI (Data Science track) # HealthConnect Experience Lab ### AnalystLab Africa Data Science Internship - Data Science Track This repository documents the Data Science track's contribution to the **HealthConnect Clinic Experience Lab**, a shared, multi-track project undertaken by AnalystLab Africa interns from Week 4 onward. ## Project Title **Improving Patient Appointment Attendance and Healthcare Support Using Data and AI** ## Business Scenario HealthConnect Clinic is a fictional healthcare provider facing several operational challenges: - Patients missing scheduled appointments (no-shows) - Difficulty understanding what drives no-show behavior - Inefficient use of appointment slots when patients fail to attend - Repetitive patient enquiries about appointments and procedures - A need to improve patient engagement and administrative support **Central Project Question:** How can HealthConnect Clinic use data and AI to reduce missed appointments and improve the patient support experience? Multiple internship tracks (Project Management, Data Analytics, Data Science, Machine Learning Engineering, and Generative AI) are contributing to this shared project, each from their own professional perspective. This repository covers the **Data Science track's** work. ## Data Science Track Role The Data Science track is responsible for defining the machine learning problem: assessing whether the available appointment data can support a no-show prediction solution, and laying the groundwork for model development in later weeks. ## Project Stages ``` Problem Understanding → Analysis & Solution Design → Development ↓ ↓ Testing & Refinement → Final Presentation ``` This repository will be updated incrementally as the project progresses through each stage. ## Week 4: Problem Understanding & ML Problem Definition Week 4 focused on understanding the business problem and defining the machine learning approach, without building or deploying a mo …