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A novel classifier for multivariate instance using graph class signatures

Frontiers of Computer Science 2020年第4期14卷 79-94页

作者： Parnika PARANJAPE Meera DHABU parag deshpande Department of Computer Science Visvesvaraya National Institute of TechnologyNagpurMaharashtra440010India

Applications like identifying different customers from their unique buying behaviours,determining ratings of a product given by users based on different sets of features,*** classification using class-specific subsets of *** of the existing state-of-the-art classifiers for multivariate data use complete feature set for classification regardless of the different class *** tree classifier can produce class-wise subsets of ***,none of these classifiers model the relationship between features which may enhance classification *** call the class-specific subsets of features and the features’interrelationships as class *** this work,we propose to map the original input space of multivariate data to the feature space characterized by connected graphs as graphs can easily model entities,their attributes,and relationships among ***,entities are modeled using graphs,where graphs occur naturally,for example,chemical ***,graphs do not occur naturally in multivariate ***,extracting class signatures from multivariate data is a challenging *** propose some feature selection heuristics to obtain class-specific prominent subgraph *** also propose two variants of class signatures based classifier namely:1)maximum matching signature(gMM),and 2)score and size of matched signatures(gSM).The effectiveness of the proposed approach on real-world and synthetic datasets has been studied and compared with other established *** results confirm the ascendancy of the proposed class signatures based classifier on most of the datasets.

关键词： multivariate instance data transformation subgraph feature selection class signatures classification

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Heme Iron Polypeptide in Iron Deficiency Anemia of Pregnancy: Current Evidence

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Open Journal of Obstetrics and Gynecology 2017年第4期7卷 420-431页

作者： Bhaskar Pal Hemant deshpande Tripura Sundari parag Biniwale Kamlesh Shah Sugandh Goel Amandeep Singh Khurana Amit Qamra Salman Motlekar Hanmant Barkate Department of Obstetrics & Gynecology Apollo Gleneagles Hospital Ltd. Kolkata India Department of Obstetrics & Gynecology Dr D.Y. Patil Medical College & Hospital Pune India Department of Obstetrics & Gynecology Krishna Institute of Medical Sciences Secunderabad India Department of Obstetrics & Gynecology Biniwale Clinic Pune India Department of Obstetrics & Gynecology Sahyadri Hospital Karad India Department of Medical Affairs Wockhardt Limited Mumbai India

Iron deficiency is the most common nutritional deficiency leading to anemia in pregnancy. Conventionally, non-heme form of iron salts has been the mainstay of treatment. However, patient compliance is an important concern with existing oral iron therapy due to gastrointestinal side effects. Heme iron, a better bioavailable and tolerable form of iron can be suitable form of iron for supplementation in pregnancy. Evidence suggests its utility in pregnancy for treatment of iron deficiency anemia with benefits extending to postpartum period. Effective transfer across placenta to fetus further supports its utility in pregnancy. This review discusses in details the absorption kinetics along with clinical evidence on efficacy, safety, and tolerability of heme-iron supplementation in iron deficiency anemia of pregnancy.

关键词： Heme Iron Pregnancy Iron Absorption Iron Deficiency Anemia

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