{'fraction_non_alphanumeric': 0.01079136690647482, 'fraction_numerical': 0.0035971223021582736, 'mean_word_length': 5.710843373493976, '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}}
Topographic Segmentation and Transit Time Estimation for Endoscopic Capsule Exams

The endoscopic capsule is a recent medical technology with important clinical benefits but suffering from a practical handicap: long exam annotation times. This paper shows how support vector machines can be used to segment the gastrointestinal tract into its four major topographic areas, allowing the automatic estimation of the clinically relevant gastric and intestinal transit times. According to medical specialists, this can reduce exam annotation times by up to 12%