Question

Data science is the multi-disciplinary field that combines statistics, mathematics, and computer science to analyze structured and unstructured data. Although data science applications, such as big data analytics and artificial intelligence, have the potential to transform health care, health care organizations face significant challenges to widespread benefits.

Discuss one example of a data science application in health care, including benefits, barriers, and recommendations for policy changes to address the barriers.

Answer 1

Data science is emerging field of 21st century and it already made its presence felt in the field of healthcare.

One example where Data science is helping in healthcare industry is assessing the patient's medical history and suggest prevention plans or risk assessment measures to avoid any further health issues.

Benefits:

Using pattern recognition and medical imaging techniques in large sets of Image data sets of patient's health conditions, data scientists were able to recognize abnormalities and underlying diseases if any.

These image data sets using Convolutional Neural Network algorithms were able to identify the patterns in the images and classify them under various categories of diseases.

Barriers:

1. Patient's data is not publicly available for everyone and there are laws to protect the privacy of the patient. However, the data available is not enough or in properly cleaned for further processing.

2. Infrastructure in hospitals is not up to the levels of where it should in regard of data science supporting platforms.

3. Hospitals are reluctant to share the data with other hospitals due to various reasons.

4. Technical expertise required to work with data science along with domain expertise of healthcare industry.

Policies are needed to share the data of patient among the data science professionals and keep the privacy of the patient at the same time.