{'fraction_non_alphanumeric': 0.01002004008016032, 'fraction_numerical': 0.0, 'mean_word_length': 5.66, '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': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Building an Expert System: A Systematic Approach to Developing an Instrument for Data Extraction From the Literature

When building an expert system that will be acceptable to clinicians in their practice, it is imperative that the knowledge engineer identifies, defines, and describes a clinical problem precisely. This can be accomplished by eliciting private knowledge from expert clinicians or by analyzing public knowledge available in the scientific literature. This study describes a systematic method for examining public knowledge found in health care textbooks and practice guidelines surrounding the concept of oral feeding in premature infants in a neonatal intensive care unit. It includes the development of an instrument for extracting data from these sources to standardize definitions of terminologies. Preliminary results and plans for further analysis are reported. This method can be applied to other clinical problems deemed appropriate for decision support system development.