{'fraction_non_alphanumeric': 0.022249690976514216, 'fraction_numerical': 0.0, 'mean_word_length': 5.377952755905512, '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}}
Reasoning mechanism of HD diagnose system based on intelligent fusion algorithm

To make patients with HD (Heart Disease) achieve standardized treatment at the same level in different medical institutions, the gap of medical quality and efficiency caused by the asymmetry of medical information and knowledge should be closed. The reasoning model based on four-layer-behavior-and-two-class-reasoning-mechanism was architected. The reasoning algorithm mixing RS (Rough Set) and PNN (Probabilistic Neural Network) was adopted to architect the heart disease intelligent diagnose system assisting the HD diagnose decision. Results of experiment shows that with the HD diagnose system mixing the RS and PNN the time to train samples was shortened and the ability to classify and generalized samples was heightened.