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Malignant middle-cerebral artery territory infarction in tuberculous vasculitis

Neuroimmunology and Neuroinflammation 2014年第1期1卷 95-97页

作者： Salvadeeswaran Meenakshi-Sundaram sundararajan srinivasan Somalinga Nagendran Karthik Suresh Pandi Alagappan Periyakaruppan Bharathi Sundar Department of Neurosciences Apollo Speciality HospitalsMadurai 625020Tamil NaduIndia Department of Radiology Apollo Speciality HospitalsMadurai 625020Tamil NaduIndia

Intracranial large vessel involvement is an unusual complication of tuberculous *** authors report a 39-year-old female presenting with an episode of seizure,followed by rapid decline in sensorium without prominent systemic *** initial cranial magnetic resonance imaging revealed tuberculomata and patchy *** antituberculous therapy,she progressively worsened.A cranial computed tomography scan done following the worsening revealed a massive middle-cerebral artery(MCA)***,the patient died in spite of decompressive *** MCA territory infarct is a rare and potentially fatal complication of tuberculous meningitis.

关键词： Arteritis malignant middle-cerebral artery territory infarct tuberculous meningitis

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A Contemporary Review on Drought Modeling Using Machine Learning Approaches

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Computer Modeling in Engineering & Sciences 2021年第8期128卷 447-487页

作者： Karpagam sundararajan Lalit Garg Kathiravan srinivasan Ali Kashif Bashir Jayakumar Kaliappan Ganapathy Pattukandan Ganapathy Senthil Kumaran Selvaraj T.Meena School of Information Technology and Engineering Vellore Institute of TechnologyVellore632014India Faculty of Information and Communication Technology University of MaltaMsidaMSD2080Malta Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterM156BHUK School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014India Centre for Disaster Mitigation and Management Vellore Institute of TechnologyVellore632014India Department of Manufacturing Engineering School of Mechanical EngineeringVellore Institute of TechnologyVellore632014India School of Civil Engineering Vellore Institute of TechnologyVellore632014India

Drought is the least understood natural disaster due to the complex relationship of multiple contributory factors. Itsbeginning and end are hard to gauge, and they can last for months or even for years. India has faced many droughtsin the last few decades. Predicting future droughts is vital for framing drought management plans to sustainnatural resources. The data-driven modelling for forecasting the metrological time series prediction is becomingmore powerful and flexible with computational intelligence techniques. Machine learning (ML) techniques havedemonstrated success in the drought prediction process and are becoming popular to predict the weather, especiallythe minimum temperature using backpropagation algorithms. The favourite ML techniques for weather forecastinginclude support vector machines (SVM), support vector regression, random forest, decision tree, logistic regression,Naive Bayes, linear regression, gradient boosting tree, k-nearest neighbours (KNN), the adaptive neuro-fuzzyinference system, the feed-forward neural networks, Markovian chain, Bayesian network, hidden Markov models,and autoregressive moving averages, evolutionary algorithms, deep learning and many more. This paper presentsa recent review of the literature using ML in drought prediction, the drought indices, dataset, and performancemetrics.

关键词： Drought forecasting machine learning drought indices stochastic models fuzzy logic dynamic method hybrid method

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