Spring-2020 Lecture series

This lecture series is part of the Asi@Connect project Intelligent Medical Services over TEIN.

Spring Lecture Series on “Machine Learning for Healthcate”, starting from April 2020, in which five lectures will be delivered on the following topics:

Machine learning will dramatically improve health care. There are already a myriad impactful ML health care applications from imaging to predicting readmissions to the back office. This lecture series will address the machine learning basics and its importance to medical domain, along with issues related to data quality enhancement. Furthermore, this lecture series will lay the foundation for understanding supervised learning and intuition behind a number of ML models along with fundamental concepts in visualization of model performance under various kinds of uncertainty.

Instructor

Wajahat Ali Khan

Assistant Professor

Kyung Hee University, South Korea

Course Content

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Lessons Status

Healthcare problems and Machine Learning solutions

This lecture will address the machine learning basics and its importance to medical domain

Data Quality Enhancement

This lecture will focus on fundamental concepts in data quality enhancement such as missing values imputation, outlier detection, normalization, etc.

Predictive Modeling for Supervised Learning

This lecture will lay the foundation for understanding supervised learning and intuition behind a number of ML models

Spring-2020 Lecture series

Course Content

Healthcare problems and Machine Learning solutions

This lecture will address the machine learning basics and its importance to medical domain

Data Quality Enhancement

This lecture will focus on fundamental concepts in data quality enhancement such as missing values imputation, outlier detection, normalization, etc.

Predictive Modeling for Supervised Learning

This lecture will lay the foundation for understanding supervised learning and intuition behind a number of ML models

Ensemble-based Model Construction

This lecture will deal with the detailed treatment of ensemble based decision tree models

Model Performance Evaluation

This lecture will address fundamental concepts in visualization of model performance under various kinds of uncertainty

Written by Usman Akhtar

Spring-2020 Lecture series

Spring-2020 Lecture series

Course Content

Healthcare problems and Machine Learning solutions This lecture will address the machine learning basics and its importance to medical domain

Data Quality Enhancement This lecture will focus on fundamental concepts in data quality enhancement such as missing values imputation, outlier detection, normalization, etc.

Predictive Modeling for Supervised Learning This lecture will lay the foundation for understanding supervised learning and intuition behind a number of ML models

Ensemble-based Model Construction This lecture will deal with the detailed treatment of ensemble based decision tree models

Model Performance Evaluation This lecture will address fundamental concepts in visualization of model performance under various kinds of uncertainty

Written by Usman Akhtar

Healthcare problems and Machine Learning solutions

This lecture will address the machine learning basics and its importance to medical domain

Data Quality Enhancement

This lecture will focus on fundamental concepts in data quality enhancement such as missing values imputation, outlier detection, normalization, etc.

Predictive Modeling for Supervised Learning

This lecture will lay the foundation for understanding supervised learning and intuition behind a number of ML models

Ensemble-based Model Construction

This lecture will deal with the detailed treatment of ensemble based decision tree models

Model Performance Evaluation

This lecture will address fundamental concepts in visualization of model performance under various kinds of uncertainty