How Big data used in the treatment of Functional Neurological Disorders (FND) - Potential PhD Topics - Phdassistance
                     HOW BIG DATA USED IN 
THE  TREATMENT OF 
FUNCTIONAL  
NEUROLOGICAL DISORDERS  
(FND) – POTENTIAL PHD  
TOPICS
An Academic presentation by
Dr. Nancy Agnes, Head, Technical Operations, Phdassistance 
 Group www.phdassistance.com
Email: [email protected]
TODAY'S 
DISCUSSION
Outline
Introduction
Functional neurological disorder - Need for big 
data:  Recent research
Future Scope
Introduction
At the intersection of neurology and psychiatry, FND is a  
prevalent condition (Perez 2021).
It is characterized by motor and sensory symptoms such 
as  tremor, limb fatigue, dystonia, numbness, and 
seizures, and it  was formerly known as conversion 
disorder.
These symptoms are associated with severe distress 
and  functional impairment and have clinical features 
that are  incompatible with other neurological/medical 
diagnoses.
Few controlled treatment trials and little research has 
been  conducted till now to assess outcomes in FND.
Due to the wide range of outcomes reported in patients with respect to a 
functional  neurological disorder, the need to study these outcomes in 
detail has become  essential (Pick 2020).
Machine learning (ML) algorithms are being used widely to collect and 
analyze  clinical neurological data.
Algorithms like Random Forest, K-Nearest Neighbour (KNN), Support 
Vector  Machine (SVM), multi-layer perception and Artificial Neural 
Network (ANN) have  shown promising results and can be further used to 
fill the gap between outcome  and treatment in FND patients.
Functional  
neurologica
l  disorder -  Despite being a commonand disablingcondition,
FND has  received little attention from the scientific 
Need for big community.
 data
Until recently, investigations involving the
pathophysiology,  etiology, and treatment of this 
cHoonwdeitvioenr,  wtheirse  hlimasi tebde.gun to change over the last few 
years  (Nicholson 2020).
Researchers from the neurology and psychiatry 
community  have conducted several research projects to 
study the outcome  of FND and are continuing to do to 
improvise their  understanding of this disorder by 
applying ML.

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 behaviors and disease attitudes, and 
altered emotional  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.
Fig. 2 : Different symptoms associated with 
FND
Recent  
Thanks to international collaborative and
research programs  activities, the field of functional community  
neuroimaging  significantly as BigData had
science in the last decade. progressed
Functional  neuroimaging methods, such asfunctional
magnetic  resonance imaging (fMRI) acquired (tfMRdIu)ring
resting-stateh e (rsfMtRaIs)k, magnetoencephalographya n(dMEG),  
electroencephalography (EEG), and other modalities are 
important  tools for studying the human brain.
They also provide methodological foundations for 
quantitative  cognitive neuroscience.
This large-scale neuroimaging big data has been 
significantly  supported by informatics infrastructure (Li 
2019).
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 in the history of disorder.
COMET (core outcome measures in effectiveness trials) has been initiated 
in  Europe that includes development instructions and a searchable 
database of  completed core outcome sets.
In the United States, the National Institute of Neurological Disorders and 
Stroke  (NINDS) is coordinating the development of a common data 
element (CDE)  resource portal to address a variety of conditions such as 
epilepsy and traumatic  brain injury (Nicholson 2020).
Table 1: Application of ML in the treatment of different neurological 
disorders
For the early diagnosis of various neurological disorders, an intelligent 
diagnostic  system has been proposed.
The five layers of this framework include, data source, big data storage, data  
preprocessing, big data analytics and disease diagnosis.
It aims to collect patient data via electronic medical records (EMRs), medical 
devices,  IoT (internet of things) devices and research centers.
This big data is then stored using different big data storage methods like, 
data  warehouse, distributed platforms, multi-dimensional storage and 
cloud storage. Next,  the preprocessing techniques are utilized to handle 
noise, missing values and remove  outliers from the data.
Contd...
Big  dataanalyticstechniques (descriptive, predictive and perspective) are
used  analyze the data effectively.
Theobtained data is thenused to conduct diagnostic analysis using ML 
algorithms  (Kaur 2020).
Contd..
.
Futur
e  
Scope When it comes to the implementation and selection
of optimal  outcome measures, FND raises unique 
q- ureasntgioen so fa n d scyhmaplletonmgess like lack of
measureme (polysymptomatic),  and outcome  and
nt  incompetent prognosis management
techniques.
These challenges can be possibly solved with the appropriate 
 implementation of big data and ML. They may be useful in 
the  diagnosis, prognosis and management of neurological 
disorders.
A diagnostic framework can be further developed and 
applied for  better management of FND.
The analysis of big data from medical and healthcare systems can be 
extremely  useful in developing new healthcare strategies.
The most recent technical advancements in data generation, processing, 
and  analysis have boosted hopes for a personalized medicine revolution 
in the near  future (Dash 2019).
Big data and high-performance computing technologies can thus reshape 
the way  we deliver healthcare and conduct research.
Contact 
Us
UNITED KINGDOM
+44-1143520021
INDIA
+91-4448137070
EMAIL
[email protected]