Benson mwangi (20 Ergebnisse)

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Personalized Psychiatry : Big Data Analytics in Mental Health
Passos, Ives Cavalcante (EDT); Mwangi, Benson (EDT); Kapczinski, Flávio (EDT)
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Taschenbuch. Zustand: Neu. Limnology of a Low Order Tropical Stream: Sagana River, Kenya | An Overview of the Structure and Function of a Low order Tropical Stream | Benson M. Mwangi | Taschenbuch | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846518113 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Personalized Psychiatry : Big Data Analytics in Mental Health
Passos, Ives Cavalcante (EDT); Mwangi, Benson (EDT); Kapczinski, Flávio (EDT)
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book integrates the concepts of big data analytics into mental health practice and research.Mental disorders represent a public health challenge of staggering proportions. According to the most recent Global Burden of Disease study, psychiatric disorders constitute the leading cause of years lost to disability. The high morbidity and mortality related to these conditions are proportional to the potential for overall health gains if mental disorders can be more effectively diagnosed and treated. In order to fill these gaps, analysis in science, industry, and government seeks to use big data for a variety of problems, including clinical outcomes and diagnosis in psychiatry. Multiple mental healthcare providers and research laboratories are increasingly using large data sets to fulfill their mission. Briefly, big data is characterized by high volume, high velocity, variety and veracity of information, and to be useful it must be analyzed, interpreted, and acted upon. As such, focus has to shift to new analytical tools from the field of machine learning that will be critical for anyone practicing medicine, psychiatry and behavioral sciences in the 21st century. Big data analytics is gaining traction in psychiatric research, being used to provide predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level.Personalized Psychiatry- Big Data Analytics in Mental Healthprovides a unique opportunity to showcase innovative solutions tackling complex problems in mental health using big data and machine learning. It represents an interesting platform to work with key opinion leaders to document current achievements, introduce new concepts as well as project the future role of big data and machine learning in mental health.…

Personalized Psychiatry: Big Data Analytics in Mental Health
Passos, Ives Cavalcante (Edited by)/ Mwangi, Benson (Edited by)/ Kapczinski, Flávio (Edited by)
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The hydrological, morphological and biological characteristics of low order mountain streams are closely linked to the catchment characteristics. Clearance and replacement of riparian vegetation with cultivated crops and tree communities may significantly affect their structure and function. This study focused on the impacts of catchment land use changes on the limnology of low order tropical streams. Striking differences were found between the two reaches, with the stream reach adjacent to the agricultural catchment exhibiting elevated and highly variable discharge and temperature regimes, conductivity, pH, ionic constituents, sediment and nutrient loads. Total litter standing stock, was however, significantly higher at the forested site (177.3 37.5 gDW.m2) than the cultivated site (81.7 32.9 gDW.m2). Total benthic macroinvertebrate abundance, diversity, evenness and species richness were higher at the cultivated stream. It is concluded that changes in catchment land use from native forestry to agriculture impacted strongly on the stream ecological conditions by causing changes on the stream morphology, hydrology, water quality and riparian vegetation composition and cover. Th 204 pp. Englisch.…

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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mwangi Benson M.Dr. Benson Mwangi is an Austrian trained Limnologist, supervised for his doctoral studies by the Late Univ. Prof. Dr. Gernot Bretschko. He currently teaches Ecology and Limnology at Kenyatta University, Kenya. He is c.…

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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The hydrological, morphological and biological characteristics of low order mountain streams are closely linked to the catchment characteristics. Clearance and replacement of riparian vegetation with cultivated crops and tree communities may significantly affect their structure and function. This study focused on the impacts of catchment land use changes on the limnology of low order tropical streams. Striking differences were found between the two reaches, with the stream reach adjacent to the agricultural catchment exhibiting elevated and highly variable discharge and temperature regimes, conductivity, pH, ionic constituents, sediment and nutrient loads. Total litter standing stock, was however, significantly higher at the forested site (177.3 ¿ 37.5 gDW.m2) than the cultivated site (81.7 ¿ 32.9 gDW.m2). Total benthic macroinvertebrate abundance, diversity, evenness and species richness were higher at the cultivated stream. It is concluded that changes in catchment land use from native forestry to agriculture impacted strongly on the stream ecological conditions by causing changes on the stream morphology, hydrology, water quality and riparian vegetation composition and cover. ThVDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 204 pp. Englisch.…

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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The hydrological, morphological and biological characteristics of low order mountain streams are closely linked to the catchment characteristics. Clearance and replacement of riparian vegetation with cultivated crops and tree communities may significantly affect their structure and function. This study focused on the impacts of catchment land use changes on the limnology of low order tropical streams. Striking differences were found between the two reaches, with the stream reach adjacent to the agricultural catchment exhibiting elevated and highly variable discharge and temperature regimes, conductivity, pH, ionic constituents, sediment and nutrient loads. Total litter standing stock, was however, significantly higher at the forested site (177.3 37.5 gDW.m2) than the cultivated site (81.7 32.9 gDW.m2). Total benthic macroinvertebrate abundance, diversity, evenness and species richness were higher at the cultivated stream. It is concluded that changes in catchment land use from native forestry to agriculture impacted strongly on the stream ecological conditions by causing changes on the stream morphology, hydrology, water quality and riparian vegetation composition and cover. Th.…

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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book integrates the concepts of big data analytics into mental health practice and research.Mental disorders represent a public health challenge of staggering proportions. According to the most recent Global Burden of Disease study, psychiatric disorders constitute the leading cause of years lost to disability. The high morbidity and mortality related to these conditions are proportional to the potential for overall health gains if mental disorders can be more effectively diagnosed and treated. In order to fill these gaps, analysis in science, industry, and government seeks to use big data for a variety of problems, including clinical outcomes and diagnosis in psychiatry. Multiple mental healthcare providers and research laboratories are increasingly using large data sets to fulfill their mission. Briefly, big data is characterized by high volume, high velocity, variety and veracity of information, and to be useful it must be analyzed, interpreted, and acted upon. As such, focus has to shift to new analytical tools from the field of machine learning that will be critical for anyone practicing medicine, psychiatry and behavioral sciences in the 21st century. Big data analytics is gaining traction in psychiatric research, being used to provide predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level.Personalized Psychiatry- Big Data Analytics in Mental Healthprovides a unique opportunity to showcase innovative solutions tackling complex problems in mental health using big data and machine learning. It represents an interesting platform to work with key opinion leaders to document current achievements, introduce new concepts as well as project the future role of big data and machine learning in mental health. 196 pp. Englisch.…

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides researchers a different way to conceptualize studies in mental health by using big-data analytics approachesOffers clinicians a broad perspective on how clinical decisions such as selection of treatment options, prevent.…

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Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Mental disorders represent a public health challenge of staggering proportions. According to the most recent Global Burden of Disease study, psychiatric disorders constitute the leading cause of years lost to disability. The high morbidity and mortality related to these conditions are proportional to the potential for overall health gains if mental disorders can be more effectively diagnosed and treated. In order to fill these gaps, analysis in science, industry, and government seeks to use big data for a variety of problems, including clinical outcomes and diagnosis in psychiatry. Multiple mental healthcare providers and research laboratories are increasingly using large data sets to fulfill their mission. Briefly, big data is characterized by high volume, high velocity, variety and veracity of information, and to be useful it must be analyzed, interpreted, and acted upon. As such, focus has to shift to new analytical tools from the field of machine learning that will be critical for anyone practicing medicine, psychiatry and behavioral sciences in the 21st century.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 196 pp. Englisch.…