Day #180 - ML In Medicine - Data Related

Today's learning is from Phd Thesis - "Improving diagnosis of acute coronary syndromes in an emergency setting: A machine learning approach"

Key Lessons

• Arteris clogged, Blood cannot transfer oxygen
• Electrocardiogram, ECG of timeseries data
• ANN - Feed the features from ECG - Output is the probability of acute cornonary syndrome
• Ensembles of Networks
• Clinical Trials

Features Selected

• Age
• Sex
• Smoking Status
• Diabetics Status
• Cholesterol Levels
• Troponin Levels

Explanation Methods

• Input Sensitivity Analysis
• Generalized Odds Ratio
• Euclidean distance measure
• Iterative input clamping

Detailed Results Study based on Clinical Trials. After this I quickly looked up for available medical datasets.

Heart Disease Data Set 
Lung Cancer Data Set
Primary Tumor Data Set 
Acute Inflammations Data Set 
Breast Cancer Wisconsin (Original) Data Set 

My Wish - These stand-alone datasets can be used to predict considering our Full Body Medical Checkup results and map it to know the probability of any disease :)



Next Talks
The Future of Machine Learning in Clinical Imaging
Case Study: TensorFlow in Medicine - Retinal Imaging (TensorFlow Dev Summit 2017)
PhD: Machine Learning for medical Image Analysis
Deep Learning in Medical Imaging - Ben Glocker
Introduction to Deep Learning, Keras, and TensorFlow
Gated-Dilated Networks for Lung Nodule Classification in CT scans

Happy Mastering DL!!!