Named-Entity Recognition for Hindi language using context pattern-based maximum entropy

This paper describes Named Entity Recognition (NER) system for Hindi language using two methodologies. An existing BaseLine Maximum Entropy-based Named Entity (BL-MENE) model and Context Pattern-based MENE (CP-MENE) framework the one proposed in this work. BL-MENE utilizes several features for the NER task but suffers from inaccurate Named Entity (NE) boundary detection, mis-classification errors, and partial recognition of NEs due to certain missing essentials. However, CP-MENE based NER task incorporates extensive features and patterns set to overcome these problems. In fact, the CP-MENE features include right-boundary, left-boundary, part-of-speech, synonyms, gazetteers and relative pronoun features. CP-MENE formulates a kind of recursive relationship to extract high ranked NE patterns that are generated through regular expressions via python@ code. Nowadays, since the Web contents in the Hindi language are rising, especially in the health-care applications, this work is conducted on the Hindi Health Data (HHD) corpus at Kaggle dataset. We conducted experiments on four NE categories- Person (PER), Disease (DIS), Consumable (CNS) and Symptom (SMP). Usually, researchers’ work upon PER NE within news articles while other NEs, especially related to the health-care domain such as DIS, CNS, and SMP NE types are left out which are incorporated in this research. CP-MENE improvised the classification performance of NEs and the F-measure achieved are 79.68% for PER, 72.50% for DIS, 68.78% for CNS, and 67.23% for SMP respectively which are comparable with respect to other NER approaches

Anesthetic management of peripartum cardiomyopathy using "epidural volume extension" technique: A case series

Peripartum cardiomyopathy is a rare cause of dilated cardiomyopathy in parturients, occurring in approximately one in 1000 deliveries, manifesting during the last few months or the first 5 months of the postpartum period. It can result in severe ventricular dysfunction during late puerperium. The major concern while managing these patients is to optimize fluid administration and avoid myocardial depression, while maintaining stable intraoperative hemodynamics. We present a case series of five parturients that were posted for elective cesarean section and managed successfully by the epidural volume extension technique