How Big data used in the treatment of (FND) - Potential PhD Topics - Phdassistance

How Big data used in the treatment of Functional Neurological Disorders (FND) – Potential PhD Topics Dr. Nancy Agnes, Head, Technical Operations, Phdassistance info@phdassistance.com

Keywords:

and it was formerly known as conversion

PhD Big Data Analytics Help, Big Data

disorder. These symptoms are associated

Research

with

Help

In

UK,

Phd

severe

distress

and

functional

Neuroscience/Neurology Research Topics

impairment and have clinical features that

Help ,Functional Neurological Disorder

are

Support, Potential PhD Research Topics

neurological/medical

Help, Neurology PhD Coursework And

controlled treatment trials and little research

Research Topics, Neuroscience Neurology

has been conducted till now to assess

Dissertation

Help

outcomes in FND. Due to the wide range of

Neurology,

outcomes reported in patients with respect to

Dissertation,

a functional neurological disorder, the need

Coursework, Editing, Manuscript Help

to study these outcomes in detail has

,Functional

Disorder,

become essential (Pick 2020). Machine

Machine Learning, Algorithm, Big Data,

learning (ML) algorithms are being used

Neuroimaging, Treatment, Neuroscience

widely to collect and analyze clinical

PhD Dissertation Topics, Neuroscience

neurological data. Algorithms like Random

Research Topics Services

Forest,

Guide

For

Neuroscience

Rewriting

Services,

Neuroscience Neurology

Neurological

incompatible

K-Nearest

with

other

diagnoses.

Few

Neighbour

(KNN),

Support Vector Machine (SVM), multi-layer I. INTRODUCTION

perception and Artificial Neural Network

At the intersection of neurology and

(ANN) have shown promising results and

psychiatry, FND is a prevalent condition

can be further used to fill the gap between

(Perez 2021). It is characterized by motor

outcome and treatment in FND patients.

and sensory symptoms such as tremor, limb fatigue, dystonia, numbness, and seizures,

Copyright © 2021 PhdAssistance. All rights reserved

1

II. FUNCTIONAL NEUROLOGICAL DISORDER - NEED FOR BIG DATA

Despite being a common and disabling

functioning, lead to worse outcomes, and lower quality of life (Pick 2020). These symptoms contribute to the poor prognosis of FND, and, thus an extensive amount of research is required in this area.

condition, FND has received little attention from

the

recently,

scientific

community.

investigations

PHYSICAL SYMPTOM : FATIGUE, SLEEP DISTURBANCE,

Until

involving

PAIN

the

PSYCHOLOGICAL SYMPTOMS : ANXIETY, DEPRESSION

pathophysiology, aetiology and treatment of this condition were limited. However, this

EMOTIONAL DISFUNCTIONING : HARMFUL COPING

has begun to change over the last few years

&

BEHAVIOURS

(Nicholson 2020). Researchers from the neurology and psychiatry community have

Fig. 2 : Different symptoms associated with FND

conducted several research projects to study the outcome of FND and are continuing to

III. RECENT RESEARCH

do to improvise their understanding of this disorder by applying ML.

Thanks

PARKINS ON'S DISEASE

international

collaborative

programs and community activities, the field

SEVERE HEADAC HE ALZHEIM ER'S DISEASE

to

EPILEPSY

of functional neuroimaging had progressed significantly as Big Data science in the last

TYPES OF NEUROLOG ICAL DISORDERS

decade. Functional neuroimaging methods, STROKE

such as functional magnetic resonance imaging (fMRI) acquired during the task

MULTIPL E SCLEROSI S

Fig. 1 : Types of neurological disorders

(tfMRI)

and

resting-state

magnetoencephalography

(rsfMRI), (MEG),

electroencephalography (EEG), and other modalities are important tools for studying

A variety of symptoms have been reported in FND patients, which complicates the prognosis and treatment of the condition. In people with FND, a wide range of physical, psychological symptoms along with potentially harmful coping behaviours and disease attitudes, and altered emotional

Copyright © 2021 PhdAssistance. All rights reserved

the

human

brain.

They also

provide

methodological foundations for quantitative cognitive neuroscience. This large-scale neuroimaging big data has been significantly

2

supported by informatics infrastructure (Li

to address a variety of conditions such as

2019).

epilepsy

and

traumatic

brain

injury

(Nicholson 2020).

SETTING UP OF BIOREPOSITORI ES

APPROPRIATE USE OF BIG DATA

TREATMENT OF FND

Fig. 3: Major components of big data and it’s application in treatment of functional neurological disorders (FND).

In the last ten years, patient groups and an international association, the functional neurological disorder society (FNDS), have emerged marking two significant milestones

Table 1: Application of ML in the

in the history of disorder. COMET (core

treatment

outcome measures in effectiveness trials)

disorders

of

different

neurological

has been initiated in Europe that includes development instructions and a searchable

For

database of completed core outcome sets. In

neurological

the United States, the National Institute of

diagnostic system has been proposed. The

Neurological Disorders and Stroke (NINDS)

five layers of this framework include, data

is coordinating the development of a

source, big data storage, data preprocessing,

common data element (CDE) resource portal

big data analytics and disease diagnosis. It

Copyright © 2021 PhdAssistance. All rights reserved

the

early

diagnosis

disorders,

an

of

various intelligent

3

aims to collect patient data via electronic

A diagnostic framework can be further

medical records (EMRs), medical devices,

developed

IoT (internet of things) devices and research

management of FND. The analysis of big

centers. This big data is then stored using

data from medical and healthcare systems

different big data storage methods like, data

can be extremely useful in developing new

warehouse, distributed platforms, multi-

healthcare strategies. The most recent

dimensional storage and cloud storage.

technical advancements in data generation,

Next, the preprocessing techniques are

processing, and analysis have boosted hopes

utilized to handle noise, missing values and

for a personalized medicine revolution in the

remove outliers from the data. Big data

near future (Dash 2019). Big data and high-

analytics techniques (descriptive, predictive

performance computing technologies can

and perspective) are used analyze the data

thus reshape the way we deliver healthcare

effectively. The obtained data is then used to

and conduct research.

and

applied

for

better

conduct diagnostic analysis using ML REFERENCE:

algorithms (Kaur 2020).

1.

IV. FUTURE SCOPE

Alickovic, E., Kevric, L., and Subasi, A. (2018).

Performance evaluation of

empirical mode

decomposition, discrete wavelet transform, and

When it comes to the implementation and

wavelet packed decomposition for automated

selection of optimal outcome measures,

epileptic

seizure

detection

and

prediction.

Biomedical signal processing and control. 39, 94-

FND raises unique questions and challenges like

-

range

(polysymptomatic),

of lack

symptoms of

102.

2.

Auger, S. D., Jacobs, B. M., Dobson, R., Marshall, C. R., & Noyce, A. J. (2021). Big data,

outcome

machine learning and artificial intelligence: a

measurement and incompetent prognosis

neurologist's guide. Practical neurology, 21(1),4-

and

11.

management

techniques.

These

challenges can be possibly solved with the

3.

Bhagya Shree, S. R., and Sheshadri, H. S. (2018).

Diagnosis of Alzheimer's disease using naive

appropriate implementation of big data and

Bayesian

ML. They may be useful in the diagnosis,

applications. 29(1), 123-132.

classifier.

Neural

computing

and

prognosis and management of neurological 4.

disorders.

Copyright © 2021 PhdAssistance. All rights reserved

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare:

4

management, analysis and future prospects.

Journal of big data, 6(1), 1-25.

10. Perez, D. L., Aybek, S., Poplirov, S., kozlowska, K., Stephen, C. D., Anderson, J., ... & American Neuropsychiatric Association Committee for

5.

Karapinar Senturk. (2020). Early diagnosis of

Research. (2021). A review and expert opinion

parkinson's disease using machine learning

on the neuropsychiatric assessment of motor

algorithms. Med hypotheses, 138, 109603-

functional neurological disorders. The journal of

109603.

neuropsyciatry and clinical neurosciences, 33(1), 14-26.

6.

Kaur, P., & Sharma, M. (2020). A smart and promising

neurological

diagnostic

11. Pick, S., Anderson, D. G., Asadi-Pooya, A. A.,

system: An amalgamation og big data, IoT, and

Aybek, S., Baslet, G., Bloem, B. R., Bradley-

emerging computing techniques. Intelligent data

Westguard, A., Brown, R. J., Carson, A. J.,

analysis:

Chalder, T., Damianova, M., David, A. S.,

from

data

disorder

gathering

to

data

comprehension, 241-246.

Edwards, M. J., Epstein, S. A., Espay, A. J., Garcin, B., Goldstein, L. H., Hallett, M.,

7.

Lhatoo, S. D., Bernasconi, N., Blumcke, I.,

Jankovic, J., Joyce, E. M.,.... Nicholson, T. R.

Braun,

S.,

(2020). Outcome measurement in functional

Galanopoulou, A., Josephson, C., Kobow, K.,

K.,

buchhalter,

J.,

Denaxas,

neurological disorder: a systematic review and

Lowenstein, D., Ryvlin, P., Schulze-Bonhage, A.,

recommendations.

sahoo, S. S., thom, M., Thurman, D., Worrell, G.,

neurosurgery, and psychiatry, 91(6), 638-649.

Journal

of

neurology,

Zhang, G. Q., & Wiebe, S. (2020). Big data in epilepsy: Clinical and research considerations.

Report from the Epilepsy Big Data Task Force of

12. Reboucus Filhoa, P. P., Sarmentoa, R. M.,

the International League Against Epilepsy.

Holandaa, G. B., and de Alencar Lima, D.

Epilepsia, 61(9), 1869-1833.

(2017).A new approach to detect and classify stroke in skull CT images via analysis of brain

8.

Li, X., Guo, N., & Li, Q. (2019). Functional

tissue densities. Computer methods and programs

neuroimaging in the new era of big data.

in biomedicine. 148, 27-43.

Genomics, proteomics & bioinformatics, 17(4),

13. Alickovic, E., Ng, E. H. N., Fiedler, L., Santurette, S., Innes-Brown, H., & Graversen, C.

393-401.

(2021). Effects of hearing aid noise reduction on 9.

Nicholson, T. R., Carson, A., Edwards, M. J.,

early

and

late

Goldstein, L. H., Hallett, M. Mildon, B., Neilsen,

competing

G., Nicholson, C., Perez, D. L., Pick, S., Stone,

Neuroscience, 15.

talkers

cortical in

representations

noise.

of

Frontiers

in

J., and the FND-COM group, & FND0COM

14. Dourado Jr, Carlos MJM, Suane Pires P. da Silva,

group collaborators are as follows (2020).

Raul Victor M. da Nobrega, Antonio Carlos da S.

Outcome measures for functional neurological

Barros, Pedro P. Reboucas Filho, and Victor

disorder:

theoretical

Hugo C. de Albuquerque. "Deep learning IoT

complexities. The journal of neuropsychiatry and

system for online stroke detection in skull

A

review

of

the

clinical neurosciences, 32(1), 33-42.

Copyright © 2021 PhdAssistance. All rights reserved

5

computed

tomography

images." Computer

Networks 152 (2019): 25-39.

Copyright © 2021 PhdAssistance. All rights reserved

6