scholarly journals Data Mining Techniques as a Tool in Neurological Disorders Diagnosis

2018 ◽  
Vol 12 (3) ◽  
pp. 217-220 ◽  
Author(s):  
Małgorzata Zdrodowska ◽  
Agnieszka Dardzińska ◽  
Monika Chorąży ◽  
Alina Kułakowska
Keyword(s):  
Data Mining ◽  
Nervous System ◽  
Neurological Disorders ◽  
Neurological Diseases ◽  
Complex Data ◽  
Complex Task ◽  
Data Mining Techniques ◽  
Rapid Pace ◽  
Mining Methods ◽  
The Brain

Abstract Neurological disorders are diseases of the brain, spine and the nerves that connect them. There are more than 600 diseases of the nervous system, such as epilepsy, Parkinson's disease, brain tumors, and stroke as well as less familiar ones such as multiple sclerosis or frontotemporal dementia. The increasing capabilities of neurotechnologies are generating massive volumes of complex data at a rapid pace. Evaluating and diagnosing disorders of the nervous system is a complicated and complex task. Many of the same or similar symptoms happen in different combinations among the different disorders. This paper provides a survey of developed selected data mining methods in the area of neurological diseases diagnosis. This review will help experts to gain an understanding of how data mining techniques can assist them in neurological diseases diagnosis and patients treatment.

scholarly journals Distribution in the brain and possible neuroprotective effects of intranasally delivered multi-walled carbon nanotubes

2021 ◽  
Author(s):  
Marzia Soligo ◽  
Fausto Maria Felsani ◽  
Tatiana Da Ros ◽  
Susanna Bosi ◽  
Elena Pellizzoni ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Nervous System ◽  
Electrochemical Properties ◽  
Biomedical Applications ◽  
Neurological Diseases ◽  
Neuroprotective Effects ◽  
Multi Walled Carbon Nanotubes ◽  
Walled Carbon Nanotubes ◽  
The Brain ◽  
Active Investigation

Carbon nanotubes (CNTs) are currently under active investigation for their use in several biomedical applications, especially in neurological diseases and nervous system injury due to their electrochemical properties.

scholarly journals Insights Into the Role of CSF1R in the Central Nervous System and Neurological Disorders

2021 ◽  
Vol 13 ◽  
Author(s):  
Banglian Hu ◽  
Shengshun Duan ◽  
Ziwei Wang ◽  
Xin Li ◽  
Yuhang Zhou ◽  
...  
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Neurological Disorders ◽  
Neurological Diseases ◽  
Colony Stimulating Factor ◽  
Loss Of Function ◽  
Axonal Spheroids ◽  
The Central Nervous System ◽  
Stimulating Factor

The colony-stimulating factor 1 receptor (CSF1R) is a key tyrosine kinase transmembrane receptor modulating microglial homeostasis, neurogenesis, and neuronal survival in the central nervous system (CNS). CSF1R, which can be proteolytically cleaved into a soluble ectodomain and an intracellular protein fragment, supports the survival of myeloid cells upon activation by two ligands, colony stimulating factor 1 and interleukin 34. CSF1R loss-of-function mutations are the major cause of adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP) and its dysfunction has also been implicated in other neurodegenerative disorders including Alzheimer’s disease (AD). Here, we review the physiological functions of CSF1R in the CNS and its pathological effects in neurological disorders including ALSP, AD, frontotemporal dementia and multiple sclerosis. Understanding the pathophysiology of CSF1R is critical for developing targeted therapies for related neurological diseases.

A Survey on Data Mining Techniques in Research Paper Recommender Systems

2019 ◽  
pp. 119-143 ◽  
Author(s):  
Benard Magara Maake ◽  
Sunday O. Ojo ◽  
Tranos Zuva
Keyword(s):  
Data Mining ◽  
Recommender Systems ◽  
Research Paper ◽  
Distance Measures ◽  
Sampling Techniques ◽  
Hidden Information ◽  
Data Mining Techniques ◽  
Reduction Methods ◽  
Mining Methods ◽  
Research Paper Recommender Systems

In this chapter, the authors give an overview of the main data mining techniques that are utilized in the context of research paper recommender systems. These techniques refer to mathematical models and tools that are utilized in discovering patterns in data. Data mining is a term used to describe a collection of techniques that infer recommendation rules and build models from research paper datasets. The authors briefly describe how research paper recommender systems' data is processed, analyzed, and then, finally, interpreted using these techniques. They review different distance measures, sampling techniques, and dimensionality reduction methods employed in computing research paper recommendations. They also review the various clustering, classification, and association rule-mining methods employed to mine for hidden information. Finally, they highlight the major data mining issues that are affecting research paper recommender systems.

Symbiotic Data Miner

2010 ◽  
pp. 1903-1908 ◽  
Author(s):  
Kuriakose Athappilly
Keyword(s):  
Data Mining ◽  
Business Intelligence ◽  
Business Environment ◽  
Evolutionary Approach ◽  
Complex Data ◽  
Data Mining Techniques ◽  
New Knowledge ◽  
Technical Professionals

Symbiotic data mining is an evolutionary approach to how organizations analyze, interpret, and create new knowledge from large pools of data. Symbiotic data miners are trained business and technical professionals skilled in applying complex data-mining techniques and business intelligence tools to challenges in a dynamic business environment.

scholarly journals Store-Operated Calcium Channels in Physiological and Pathological States of the Nervous System

2020 ◽  
Vol 14 ◽  
Author(s):  
Isis Zhang ◽  
Huijuan Hu
Keyword(s):  
Nervous System ◽  
Calcium Channels ◽  
Neurological Disorders ◽  
Neurological Diseases ◽  
Physiological Role ◽  
The Body ◽  
Store Operated Calcium Entry ◽  
Important Pathway ◽  
Molecular Components

Store-operated calcium channels (SOCs) are widely expressed in excitatory and non-excitatory cells where they mediate significant store-operated calcium entry (SOCE), an important pathway for calcium signaling throughout the body. While the activity of SOCs has been well studied in non-excitable cells, attention has turned to their role in neurons and glia in recent years. In particular, the role of SOCs in the nervous system has been extensively investigated, with links to their dysregulation found in a wide variety of neurological diseases from Alzheimer’s disease (AD) to pain. In this review, we provide an overview of their molecular components, expression, and physiological role in the nervous system and describe how the dysregulation of those roles could potentially lead to various neurological disorders. Although further studies are still needed to understand how SOCs are activated under physiological conditions and how they are linked to pathological states, growing evidence indicates that SOCs are important players in neurological disorders and could be potential new targets for therapies. While the role of SOCE in the nervous system continues to be multifaceted and controversial, the study of SOCs provides a potentially fruitful avenue into better understanding the nervous system and its pathologies.

Analysis of flight delays in aviation system using different classification algorithms and feature selection methods

2019 ◽  
Vol 123 (1267) ◽  
pp. 1415-1436 ◽  
Author(s):  
A. B. A. Anderson ◽  
A. J. Sanjeev Kumar ◽  
A. B. Arockia Christopher
Keyword(s):  
Data Mining ◽  
Feature Selection ◽  
Classification Model ◽  
System Level ◽  
Support Vector ◽  
Flight Delays ◽  
Data Mining Techniques ◽  
Mining Methods ◽  
Artificial Neural Network Ann ◽  
Aircraft System

ABSTRACTData mining is a process of finding correlations and collecting and analysing a huge amount of data in a database to discover patterns or relationships. Flight delay creates significant problems in the present aviation system. Data mining techniques are desired for analysing the performance in which micro-level causes propagate to make system-level patterns of delay. Analysing flight delays is very difficult – both when looking from a historical view as well as when estimating delays with forecast demand. This paper proposes using Decision Tree (DT), Support Vector Machine (SVM), Naive Bayesian (NB), K-nearest neighbour (KNN) and Artificial Neural Network (ANN) to study and analyse delays among aircrafts. The performance of different data mining methods is found in the different regions of the updated datasets on these classifiers. Finally, the result shows a significant variation in the performance of different data mining methods and feature selection for this problem. This paper aims to deal with how data mining techniques can be used to understand difficult aircraft system delays in aviation. Our aim is to develop a classification model for studying and reducing delay using different data mining methods and, in this manner, to show that DT has a greater classification accuracy. The different feature selectors are used in this study in order to reduce the number of initial attributes. Our results clearly demonstrate the value of DT for analysing and visualising how system-level effects happen from subsystem-level causes.

Symbiotic Data Mining

2011 ◽  
pp. 1083-1086
Author(s):  
Kuriakose Athappilly ◽  
Alan Rea
Keyword(s):  
Data Mining ◽  
Business Intelligence ◽  
Business Environment ◽  
Evolutionary Approach ◽  
Complex Data ◽  
Data Mining Techniques ◽  
New Knowledge ◽  
Technical Professionals

Symbiotic data mining is an evolutionary approach to how organizations analyze, interpret, and create new knowledge from large pools of data. Symbiotic data miners are trained business and technical professionals skilled in applying complex data-mining techniques and business intelligence tools to challenges in a dynamic business environment.

scholarly journals Locus Coeruleus Magnetic Resonance Imaging in Neurological Diseases

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Alessandro Galgani ◽  
Francesco Lombardo ◽  
Daniele Della Latta ◽  
Nicola Martini ◽  
Ubaldo Bonuccelli ◽  
...  
Keyword(s):  
Locus Coeruleus ◽  
Neurological Disorders ◽  
Potential Role ◽  
Neurological Diseases ◽  
Mri Findings ◽  
Promising Tool ◽  
Experimental Tool ◽  
Early Biomarker ◽  
The Brain

Abstract Purpose of Review Locus coeruleus (LC) is the main noradrenergic nucleus of the brain, and its degeneration is considered to be key in the pathogenesis of neurodegenerative diseases. In the last 15 years,MRI has been used to assess LC in vivo, both in healthy subjects and in patients suffering from neurological disorders. In this review, we summarize the main findings of LC-MRI studies, interpreting them in light of preclinical and histopathological data, and discussing its potential role as diagnostic and experimental tool. Recent findings LC-MRI findings were largely in agreement with neuropathological evidences; LC signal showed to be not significantly affected during normal aging and to correlate with cognitive performances. On the contrary, a marked reduction of LC signal was observed in patients suffering from neurodegenerative disorders, with specific features. Summary LC-MRI is a promising tool, which may be used in the future to explore LC pathophysiology as well as an early biomarker for degenerative diseases.

scholarly journals Intranasal Delivery of Nanoformulations: A Potential Way of Treatment for Neurological Disorders

Molecules ◽  
2020 ◽  
Vol 25 (8) ◽  
pp. 1929 ◽  
Author(s):  
Salman Ul Islam ◽  
Adeeb Shehzad ◽  
Muhammad Bilal Ahmed ◽  
Young Sup Lee
Keyword(s):  
Drug Delivery ◽  
Neurological Disorders ◽  
Neurological Diseases ◽  
Nasal Delivery ◽  
Intranasal Route ◽  
Drug Molecules ◽  
Surface Enhanced ◽  
Effective Delivery ◽  
The Central Nervous System ◽  
The Brain

Although the global prevalence of neurological disorders such as Parkinson’s disease, Alzheimer’s disease, glioblastoma, epilepsy, and multiple sclerosis is steadily increasing, effective delivery of drug molecules in therapeutic quantities to the central nervous system (CNS) is still lacking. The blood brain barrier (BBB) is the major obstacle for the entry of drugs into the brain, as it comprises a tight layer of endothelial cells surrounded by astrocyte foot processes that limit drugs’ entry. In recent times, intranasal drug delivery has emerged as a reliable method to bypass the BBB and treat neurological diseases. The intranasal route for drug delivery to the brain with both solution and particulate formulations has been demonstrated repeatedly in preclinical models, including in human trials. The key features determining the efficacy of drug delivery via the intranasal route include delivery to the olfactory area of the nares, a longer retention time at the nasal mucosal surface, enhanced penetration of the drugs through the nasal epithelia, and reduced drug metabolism in the nasal cavity. This review describes important neurological disorders, challenges in drug delivery to the disordered CNS, and new nasal delivery techniques designed to overcome these challenges and facilitate more efficient and targeted drug delivery. The potential for treatment possibilities with intranasal transfer of drugs will increase with the development of more effective formulations and delivery devices.

scholarly journals Mining on Social Media Data: To Determine the Personality of Unrevealed Person

2019 ◽  
Vol 8 (4) ◽  
pp. 8574-8577
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Information Mining ◽  
Social Media Data ◽  
Data Mining Techniques ◽  
Network Discovery ◽  
The Social ◽  
Mining Methods ◽  
Using Data ◽  
Media Data

The unavoidable utilization of online networking like Facebook is giving exceptional measures of social information. Information mining methods have been broadly used to separate learning from such information. The character of the person is predicted whether he is good or not by using data mining techniques from user self-made data. Mining methods are being broadly using to separate learning from such information, main examples for them are network discovery and slant investigation. Notwithstanding, there is still a lot of room to investigate as far as the occasion information (i.e., occasions with timestamps, for example, posting an inquiry, altering an article in Wikipedia, and remarking on a tweet. These occasions react users' personal conduct standards and working forms in the social media websites.

Sign in / Sign up

Export Citation Format

Share Document