{'fraction_non_alphanumeric': 0.026602176541717048, 'fraction_numerical': 0.0, 'mean_word_length': 5.043795620437956, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Introduction to clinical decision making.

In the last few years there has been a remarkable increase in the amount of clinical data in the average hospital chart, and more and more problem-solving algorithms have been developed. We need better "thinking tools" to help us handle the flow of information. The term "clinical decision making" is used to describe a systematic way to handle data and algorithms to decide on a best course of action. This introductory article discusses some of the problems in establishing a decision criterion, both for a population and for an individual patient. Comparing the probabilities and utilities of various diagnostic outcomes (true positive, false positive, etc.) leads to a diagnostic strategy. The article also discusses conditional probability. Bayes' theorem, and likelihood ratios.