Download Analyzing Patient Interactions within Cancer

Analyzing Patient Interactions
within Cancer Support Groups
Zhenghao Chen, Pang Wei Koh
Together with:
Marc Rasi, Suchi Saria, Daphne Koller
Katy Plant, Philip Ritter and Kate Lorig
Cancer
• Leading cause of death in the developed world
• Treatment:
• Chemotherapy
• Surgery
• Radiotherapy
very debilitating!
• Threat of recurrence
• Management of cancer survivors is important
Traditional Peer Support Groups
Online Peer Support Groups
Some Questions
1. Do online support groups work?
2. Can we discover better clinical practices?
3. Can we predict health outcomes more
accurately?
Sentiment Trends
Sentiment-Topic Association
• cancer treatment years year breast chemo back
recurrence months treatments pain diagnosis
diagnosed oncologist ll finished dx told doctor
• side therapy scan don blood scars lymphedema
radiation onc scar eects arm surgeon results
physical reconstruction follow doctor pain
• love kids year mom cat joy dogs years cats
husband son home watching funny place sound
house christmas watch
Sentiment-Topic Association
• sleep bed night work hours sleeping nights
stressed trouble earlier early late schedule tired
morning ready music problems times
• plan action week peggy great days tools plans
specific make session exercise walking
confidence level completing time good complete
Outcome Prediction
90
80
70
60
50
Baseline
Augmented
40
30
20
10
0
Absolute
Change
Conclusion
• Data from online groups is plentiful and
untapped
• It seems to work even with a small dataset
• Scaling up might help us improve clinical
outcomes for cancer patients