Ceyda Oksel|Sadia Haider|Sara Fontanella|Clément Frainay|Adnan ?ustovi?
Classification of Pediatric Asthma: From Phenotype Discovery to Clinical Practice
Imperial College London|Imperial College London|Imperial College London|Toxalim Research Centre in Food Toxicology|Imperial College London|Imperial College London
advances big data analytics created opportunity step change unraveling mechanisms underlying development complex diseases asthma providing valuable insights drive better diagnostic decisionmaking clinical practice opening paths individualized treatment plans however translating findings datadriven analyses meaningful insights actionable solutions requires approaches tools move beyond mining patterning longitudinal data purpose review summarize recent advances phenotyping asthma discuss key hurdles currently hampering translation phenotypic variation mechanistic insights clinical setting suggest potential solutions may address limitations accelerate moving discoveries practice order advance field phenotypic discovery greater focus placed investigating extent withinphenotype variation advocate cautious modeling approach supervising findings delineate precisely characteristics individual trajectories assigned phenotype furthermore important employ different methods within study compare stability derived phenotypes assess immutability individual assignments phenotypes make step change toward precision stratified personalized medicine capitalize available big data assets develop genuine crossdisciplinary collaborations wherein data scientists turn data information using algorithms machine learning team medical professionals provide deep insights specific subjects clinical perspective