Machine learning & Artificial Intelligence (AI)

Traditional analytics tools may not be suited to capturing the full value of big healthcare data, as either data dimension is too large for a comprehensive analysis, or relationships among variables are too complicated to derive, rendering most of the value buried in the raw data.

Machine learning & AI are novel methods of data analysis that automates analytical modeling, feature selection and predictive analytics. We have >10 years of experience in applying support vector machine (SVM) models to biomedical problems. In addition, we are able to implement TensorFlow, an AI package emerging in recent years.

However, applying machine learning models is not straightforward, as data extraction and normalization has big effects and overfitting often occurs. Construciton of valid and practical machine learning models needs the assistence of experienced data scientists like us.

Please check our project samples below:

PySpark SVM model for classifying tumor and normal samples

Deep Learning (TensorFlow) for precision medicine modeling

Machine learning models for bank telemarketing

Convolutional Neural Network image classifier