Abstract
Patient Similarity: Emerging Concepts in Systems and Precision Medicine.
Highlights
Healthcare data generates a huge volume of information in various formats at high velocity with sometimes questionable veracity (Barkhordari and Niamanesh, 2015) (4V)
Patient similarity is in its early stages, information about diseases, risk factors, lifestyle habits, medication use, co-morbidities, molecular and histopathological information, hospitalizations, or death are compared with laboratory investigations, imaging, and other clinical data assessing medical evidence of human behavior (Figure 1)
For illustration of the utility of patient similarity in medicine, only briefly presented here are a few selected examples of patient similarity analytics used for diabetes and cancer, which are common chronic or terminal diseases, respectively, currently addressed in public health
Summary
Healthcare data generates a huge volume of information in various formats at high velocity with sometimes questionable veracity (Barkhordari and Niamanesh, 2015) (4V). Patient similarity is in its early stages, information about diseases, risk factors, lifestyle habits, medication use, co-morbidities, molecular and histopathological information, hospitalizations, or death are compared with laboratory investigations, imaging, and other clinical data assessing medical evidence of human behavior (Figure 1). Such analytics consist of efficient computational analyses with patient stratification by multiple co-occurrence statistics, based on clinical characteristics. Patient similarity analytics are not restricted to global findings from large clinical trials consisting of somewhat heterogeneous patient populations (Roque et al, 2011) In this way, patient similarity represents a paradigm shift that introduces disruptive innovation to optimize personalization of patient care. Patient Similarity in Systems Medicine (Buske et al, 2015a), congenital malformations (Buske et al, 2015a), and various other conditions or factors influencing health status (Gotz et al, 2012; Subirats et al, 2012; Ng et al, 2015)
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