Machine Learning & Artificial Intelligence · Medical AI & Healthcare Imaging

Medical artificial intelligence: clinical machine learning

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction // Bioinformatics and Precision Health Analytics

Overview

Topics covered

  • Introduction
  • Medical Artificial Intelligence: Stochastic Modeling and Clinical Machine Learning
  • Introduction and the Transition from Classical Biostatistics to Clinical Machine Learning
  • Clinical Data Structures and the Electronic Health Record (EHR)
  • Advanced Imputation Mechanisms in Medicine
  • Multiple Imputation by Chained Equations (MICE)

Related concepts

Main connections

  • Survival analysis & Kaplan-Meier
  • Regularization (Lasso / Ridge / Elastic Net)
  • Maximum likelihood estimation
  • Overfitting & cross-validation
  • Missing data & multiple imputation
  • Model interpretability (SHAP / LIME)

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

𝒯i={(ti,1,𝐱i,1),(ti,2,𝐱i,2),…,(ti,k,𝐱i,k)}
View LaTeX source\mathcal{T}_i = \left\{ (t_{i,1}, \mathbf{x}_{i,1}), (t_{i,2}, \mathbf{x}_{i,2}), \dots, (t_{i,k}, \mathbf{x}_{i,k}) \right\}