Article Bias: The article presents a study on improving patient phenotyping using automated processing of discharge summaries in healthcare, focusing on the use of natural language processing to enhance clinical data, thereby remaining largely factual and objective with little overt bias.
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ðïļ Objective <â> Subjective ðïļ :
ðĻ Sensational:
ð Prescriptive:
ðĻ Fearful:
ð Begging the Question:
ðĢïļ Gossip:
ð Opinion:
ðģ Political:
Oversimplification:
ðïļ Appeal to Authority:
ðž Immature:
ð Circular Reasoning:
ð Covering Responses:
ðĒ Victimization:
ðĪ Overconfident:
ðïļ Spam:
â Ideological:
ð Negative <â> Positive ð:
ðð Double Standard:
â Uncredible <â> Credible â :
ð§ Rational <â> Irrational ðĪŠ:
ðĪ Advertising:
ðŽ Scientific <â> Superstitious ðŪ:
ðĪ Written by AI:
ð Low Integrity <â> High Integrity âĪïļ:
AI Bias: Neutral to scientific, focusing on data-driven analysis.
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