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DATA
Machine Learning (Outcomes
Avg. A1C reduction
BP management
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DATA
Machine Learning
Disease and Medication Data
From the physician/hospital
Disease Information
NYHA Class
HFrEF, HFpEF, HFmrEF
Duration since diagnosis
Last discharge
Other chronic conditions
Other risk factors
List of medications and dosages
Treatment Adherence Data
Patient reported adherence data
Medication adherence (daily)
Dietary Information(daily)
Emotional wellness (Sentiment Analyzer)
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Disease Progression Data
Heart Failure Symptoms Tracker
Edema
Shortness of breath
Chronic coughing/wheezing
Fatigue
Nausea
Impaired thinking
High heart rate
Social Determinants of Health
Conversational Data
Barriers to get medication (cost, insurance, access)
Other priorities
Behavioral
Behavior Change Models
Triggers, Motivations, Ability to adapt
Warriors
Strivers
Strugglers
Ennegram Personalities Classification
Social Support Group Engagement
The Reformer
The Helper
The Achiever
The Individualist
The Investigator
The Loyalist
The Enthusiast
The Challenger
The Peacemaker
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Data needs to be rich, robust
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What are the factors that drive variance in persistence and adherence (co-morbidity, gender, SDoH)
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