1. Soft Internet Sensors for Cancer Analytics
Neel Sonsale Boyang Ren Hiroki Yokota Zina Ben Miled
Data Analytics
 Examining huge amounts of data to uncover patterns,
find correlations, influencers and useful information
in order to make the best possible decisions.
 Used mainly by organizations to collect and
understand the important information present in
large volumes of data.
Data Analytics in Healthcare
 Healthcare industry generates vast amounts of data
which includes records, compliance and regulatory
requirements and patient care.
 Social media is also becoming a noticeable source of
customer sentiments related to treatment and
diagnosis
 Potential for big data analytics in healthcare to lead
to better outcomes across various scenarios including
identifying effective treatments, post-treatment
management and general treatment response.
Using Social Media
 Social media, such as blogs, tweets, and Facebook posts, can
be used to gather disease related information.
 Recently, the above data has been gathered through a one
time process which is inadequate due to the velocity of the
data in the above sources.
 We propose to implement a framework consisting of
dynamic software sensors that would
 Collect relevant information from social media
 Build upon previously collected knowledge in order to
dynamically refine the findings
 Develop new investigation lines based on new trends in
social medial
 Enable sensors to identify the frequency and the relevance
of the sources being interrogated.
 Enable sensors to identify influencers and connectors
within a given source or across sources.
 Big Data in Healthcare is important because of the
diversity of data types and the velocity of this data.
 Healthcare, and the community at large will benefit
from knowledge gathered over time through
sophisticated analytical tools and algorithms that are
tailor-made to a specific disease.BIG DATA
DATA
DISCOVERY
DATA
ANALYSIS PATTERNS
- Public Health
Research
Databases
- Patient records
Internet
of
Sensors
Improved
Treatment
Decisions and
Lower
Treatment Cost
Data Analytics in Breast Cancer
 About 1 in 8 women in U.S. will develop breast
cancer with an estimated 231,840 new cases in the
year 2015.
 Big data and related data analytics can play a major
role in developing a better understanding of the
symptoms of the disease and the management of the
general health care of the patients in the pre-
treatment and post-treatment phases .
 Big Data can also provide useful insights into the
segregation of the efficacy of the treatments across
social environments, a factor which is normally hard
to include in traditional clinical study.
Identifying
Connectors
Sentiment
Analysis
Investigate
Patients
Behavior
Identifying
Major
Influencers
Conclusion
 Big data analytics has the potential to help healthcare
providers and patients make better treatment decisions.
 The proposed Internet of Sensors for disease related
information from social media sources can derive the
required knowledge on a large scale and can adapt efficiently
to the velocity and variety of these sources.