Multi-Class Classifier in Parkinson’s Disease Using an Evolutionary Multi-Objective Optimization Algorithm

Line nr.

Text in former contribution

Revised version

5

Each of these VOIs is subjected to volumetric feature extraction using the Discrete Wavelet Transform (3D-DWT).

Each of these VOIs is subjected to volumetric feature extraction using the Three-Dimensional Discrete Wavelet Transform (3D-DWT).

11

In order to analyze the accuracy obtained in the SVM classifier

In order to analyze the SVM classifier accuracy

13

 in the multi-class classification

 in multi-class classification

20

Dementia is a disease characterized by the deterioration of brain functions.

Dementia is a clinical syndrome characterized by a progressive deterioration of cognitive functions.

21

Currently, the research of brain diseases and dementia is one of the most important fields of research.

Currently, research in brain diseases and dementia is one of the most important fields of investigation.

28

 due to the aging of the population

 due to the ageing of the population

30

These figures show…

34

that make it possible to slow down the development of the disease

that slow down the development of PD

35

a prolonged period

a more extended period of time

43

incoordination

lack of coordination

52

wherein rigidity inflexibility and in the legs makes the patient suffering from the disease barely have motor ability to walk \cite{Kalia2015}..

wherein rigidity and inflexibility in the legs makes the patient barely have motor ability to walk \cite{Kalia2015}.

53

The methodology usually used in the diagnosis of PD

The methodology usually used in PD diagnosis

60

with early PD

in early stages of PD

73

MRI is a technique that has been used to study abnormal brain function in a variety of diseases.

(Delete sentence, as it is the same idea as the following sentence).

74

that has been used fruitfully

that has been fruitfully applied

81

Using the most relevant regions, an intelligent classifier, based on Support Vector Machine (SVM), is constructed the intention of being

Using the most relevant regions, an intelligent classifier based on Support Vector Machine (SVM), is constructed with the aim of being

84

(multiclass classification: Parkinson's, prodomal,  SWEED and normal patients)

(multiclass classification: Parkinson's disease, prodomal,  SWEDD, gene cohort and normal patients)

92

measure the initial contact to final contact of the same foot when walking and were observed as an consequence of central pattern generators established by spinal circuits

measure the initial to final contact of the same foot when walking and were observed as a consequence of central pattern generators established by spinal circuits

97

being a important

being an important

126

The MRI analysis for PD diagnosis is a very fruitful area of research, where in recent years, relevant papers have appeared developing novel methodologies

MRI analysis for PD classification is a very fruitful area of research, indeed in recent years many relevant papers have been published developing novel methodologies

128

Most of the articles sent in the bibliography focus on the realization of binary classifiers in order to determine control patients and PD patients

Most of the articles cited in the bibliography focus on the realization of binary classifiers in order to differentiate between control and PD patients

144

The data used was acquired

Input data was acquired

148

The authors

Authors

162

In recent years, Convolutional Neural Networks (CNN) has been extensively used

In recent years, Convolutional Neural Networks (CNN) have been extensively used

164

For example, in Sivaranjini et al. \cite{Sivaranjinia2020} MR images Parkinson's disease subjects  and healthy control volunteers using DL neural network was used, showing an accuracy of 88.9\%, based on the PPMI data-set.

For example, in Sivaranjini et al. \cite{Sivaranjinia2020} MR images of Parkinson's disease subjects and healthy control volunteers were classified by a  DL neural network, showing an accuracy of 88.9\%, based on the PPMI data-set.

182

To the best of our knowledge there are very few, if not almost no, references in the literature

To the best of our knowledge, there are very few, if any, references in the literature

188

the reduction of the dimensionality of the problem

dimensionality reduction of the problem

189

using mRMR and PCA

applying mRMR and PCA

205

 (4) Use the trained SVM classifier (from training steps with selected VOI), with test samples

 (4) Classification of test samples through the SVM classifier previously trained with selected VOI

206

 block scheme the test phase

 block scheme of the test phase

217

Phase 2: The block scheme for test phase

Phase 2: Block scheme for the test phase

232

 maintaining the assumption that SWEDD patients have another motor disorder

 maintaining the assumption that SWEDD patients suffer from another motor disorder

245

We must emphasize that  exist patient having multiple NIfTI files

It must be emphasized that there are patients having multiple NIfTI files

254

The third group analysed

(New paragraph) The third group which was analysed

269

The first step consisted in the elimination of those duplicated or corrupted images. The final set images is reduced to a total of 917 MRI images, for the four types of patients analysed.

The first step consisted in the elimination of duplicated and corrupted images. Afterwards, the set of images was reduced to a total of 917 MRI images, corresponding to the five types of patients that were analysed.

270

SWEED group

SWEDD group

276

deviation of age and weight

age and weight standard deviation

279

Weight (Tables 1-3)

Weight (kg)

299

Although the noise that an image may have

Although the noise that can be present in an image

301

the performance of an automatic image prepossessing methodology and, therefore, it requires removal.

the performance of an automatic image preprocessing methodology and, therefore, it requires removal.

305

This features (as a real number vector)

These features (as a real number vector)

340

For example, Figure \ref{fig:wavelet} show a two level of the decomposition for an brain image.

For example, Figure \ref{fig:wavelet} shows a two level decomposition for a brain image.

352

Additionally, a better understanding of the disease by characterizing the most relevant regions of the brain for the construction of the classifier.

Additionally, a better understanding of the disease is expected by characterizing the most relevant regions of the brain for the construction of the classifier.

377

When treating a volumetric magnetic resonance image, various procedures must be performed filters

When a volumetric magnetic resonance image is being processed, various filtering procedures must be performed

388

This paper address a classification problem, in with there exist multi-class ($C$ classes) for each patterns.

This paper addresses a classification problem where there exist multi-class ($C$ classes) for each pattern.

400

any information about of $v_j$

any information about $v_j$

407

Determining which is the appropriate discretization is not easy task for specific problem, using in this case other

Determining the appropriate discretization is not an easy task for this specific problem. In this case, other estimation methods of density functions as maximum likelihood, Bayesian estimation or non-parametric techniques were used.

414

is not easly to be computed

is difficult to be computed due to the fact

416

In this way the insufficiency of data for the estimation of the density functions would be covered and their calculation would be would be carried out

In this way, the lack of data for the estimation of the density functions would be solved and their calculation would be carried out

420

the set of variables based on in

the set of variables based on

432

is defined as

is defined as:

438

Assuming found the suboptimal set $S_{m−1}$ of $m−1$ variables,

Assuming the suboptimal set $S_{m−1}$ of $m−1$ variables to be found,

439

to add

to be added

443

thousand

thousands

446

Indicate that

It should be noted that

462

an Multi-Objective Optimization Evolutionary

a Multi-Objective Optimization Evolutionary

468

 is represented by a chromosome, and said chromosome is made up of different genes

 is represented by a chromosome, which is made up of different genes

479

 when said VOI is not used

 when that VOI is not used

490

The population size used in the simulation carried out was 250.

The population size that was used in the simulation was 250.

495

that have their value to one

that are set to one

496

elist strategy:

elitist strategy:

513

typically the maximum number of generations exceeded

typically, a maximum number of generations is reached

518

 (measured as the number of VOIs used )

 (measured as the number of needed VOIs).

524

like the one presented in the figure

like the one presented in Figure \ref{fig:Solution_ParetoFront}

530

a feature reduction is performed

a feature reduction procedure is performed

553

and test phase of the SVM classifier obtained

and a test phase of the obtained SVM classifier

558

potential solutions, called chromosome

i.e. potential solutions, called chromosomes

564

execution times

execution time

575

In multi-class problems is frequently used the confusion matrix

In multi-class problems the confusion matrix  is frequently used

591

the precision decreases

precision decreases

618

As was presented

As it was described

632

shows the location

show the location

637

It is relevant to make a comparison of the results in classification of PD disease

It is relevant to make a comparison of the PD disease classification results

642

Regions of the brain selected (Fig. 14-15)

Selected brain regions

644

The novel methodology presented

The novel presented methodology

645

classification of Parkinson's disease is of relevance to expert neurologists

classification of Parkinson's disease is of great relevance to expert neurologists

647

Obtaining the most relevant VOI was thanks to the implementation

Obtaining the most relevant VOIs was accomplished due to the implementation

677

The results obtained in the confusion matrices, for the different solutions of the MOE analyzed,

Results from the confusion matrices for the different solutions of the analyzed MOE

Line nr.

Text in former contribution

Revised version

5

Each of these VOIs is subjected to volumetric feature extraction using the Discrete Wavelet Transform (3D-DWT).

Each of these VOIs is subjected to volumetric feature extraction using the Three-Dimensional Discrete Wavelet Transform (3D-DWT).

11

In order to analyze the accuracy obtained in the SVM classifier

In order to analyze the SVM classifier accuracy

13

 in the multi-class classification

 in multi-class classification

20

Dementia is a disease characterized by the deterioration of brain functions.

Dementia is a clinical syndrome characterized by a progressive deterioration of cognitive functions.

21

Currently, the research of brain diseases and dementia is one of the most important fields of research.

Currently, research in brain diseases and dementia is one of the most important fields of investigation.

28

 due to the aging of the population

 due to the ageing of the population

30

These figures show…

34

that make it possible to slow down the development of the disease

that slow down the development of PD

35

a prolonged period

a more extended period of time

43

incoordination

lack of coordination

52

wherein rigidity inflexibility and in the legs makes the patient suffering from the disease barely have motor ability to walk \cite{Kalia2015}..

wherein rigidity and inflexibility in the legs makes the patient barely have motor ability to walk \cite{Kalia2015}.

53

The methodology usually used in the diagnosis of PD

The methodology usually used in PD diagnosis

60

with early PD

in early stages of PD

73

MRI is a technique that has been used to study abnormal brain function in a variety of diseases.

(Delete sentence, as it is the same idea as the following sentence).

74

that has been used fruitfully

that has been fruitfully applied

81

Using the most relevant regions, an intelligent classifier, based on Support Vector Machine (SVM), is constructed the intention of being

Using the most relevant regions, an intelligent classifier based on Support Vector Machine (SVM), is constructed with the aim of being

84

(multiclass classification: Parkinson's, prodomal,  SWEED and normal patients)

(multiclass classification: Parkinson's disease, prodomal,  SWEDD, gene cohort and normal patients)

92

measure the initial contact to final contact of the same foot when walking and were observed as an consequence of central pattern generators established by spinal circuits

measure the initial to final contact of the same foot when walking and were observed as a consequence of central pattern generators established by spinal circuits

97

being a important

being an important

126

The MRI analysis for PD diagnosis is a very fruitful area of research, where in recent years, relevant papers have appeared developing novel methodologies

MRI analysis for PD classification is a very fruitful area of research, indeed in recent years many relevant papers have been published developing novel methodologies

128

Most of the articles sent in the bibliography focus on the realization of binary classifiers in order to determine control patients and PD patients

Most of the articles cited in the bibliography focus on the realization of binary classifiers in order to differentiate between control and PD patients

144

The data used was acquired

Input data was acquired

148

The authors

Authors

162

In recent years, Convolutional Neural Networks (CNN) has been extensively used

In recent years, Convolutional Neural Networks (CNN) have been extensively used

164

For example, in Sivaranjini et al. \cite{Sivaranjinia2020} MR images Parkinson's disease subjects  and healthy control volunteers using DL neural network was used, showing an accuracy of 88.9\%, based on the PPMI data-set.

For example, in Sivaranjini et al. \cite{Sivaranjinia2020} MR images of Parkinson's disease subjects and healthy control volunteers were classified by a  DL neural network, showing an accuracy of 88.9\%, based on the PPMI data-set.

182

To the best of our knowledge there are very few, if not almost no, references in the literature

To the best of our knowledge, there are very few, if any, references in the literature

188

the reduction of the dimensionality of the problem

dimensionality reduction of the problem

189

using mRMR and PCA

applying mRMR and PCA

205

 (4) Use the trained SVM classifier (from training steps with selected VOI), with test samples

 (4) Classification of test samples through the SVM classifier previously trained with selected VOI

206

 block scheme the test phase

 block scheme of the test phase

217

Phase 2: The block scheme for test phase

Phase 2: Block scheme for the test phase

232

 maintaining the assumption that SWEDD patients have another motor disorder

 maintaining the assumption that SWEDD patients suffer from another motor disorder

245

We must emphasize that  exist patient having multiple NIfTI files

It must be emphasized that there are patients having multiple NIfTI files

254

The third group analysed

(New paragraph) The third group which was analysed

269

The first step consisted in the elimination of those duplicated or corrupted images. The final set images is reduced to a total of 917 MRI images, for the four types of patients analysed.

The first step consisted in the elimination of duplicated and corrupted images. Afterwards, the set of images was reduced to a total of 917 MRI images, corresponding to the five types of patients that were analysed.

270

SWEED group

SWEDD group

276

deviation of age and weight

age and weight standard deviation

279

Weight (Tables 1-3)

Weight (kg)

299

Although the noise that an image may have

Although the noise that can be present in an image

301

the performance of an automatic image prepossessing methodology and, therefore, it requires removal.

the performance of an automatic image preprocessing methodology and, therefore, it requires removal.

305

This features (as a real number vector)

These features (as a real number vector)

340

For example, Figure \ref{fig:wavelet} show a two level of the decomposition for an brain image.

For example, Figure \ref{fig:wavelet} shows a two level decomposition for a brain image.

352

Additionally, a better understanding of the disease by characterizing the most relevant regions of the brain for the construction of the classifier.

Additionally, a better understanding of the disease is expected by characterizing the most relevant regions of the brain for the construction of the classifier.

377

When treating a volumetric magnetic resonance image, various procedures must be performed filters

When a volumetric magnetic resonance image is being processed, various filtering procedures must be performed

388

This paper address a classification problem, in with there exist multi-class ($C$ classes) for each patterns.

This paper addresses a classification problem where there exist multi-class ($C$ classes) for each pattern.

400

any information about of $v_j$

any information about $v_j$

407

Determining which is the appropriate discretization is not easy task for specific problem, using in this case other

Determining the appropriate discretization is not an easy task for this specific problem. In this case, other estimation methods of density functions as maximum likelihood, Bayesian estimation or non-parametric techniques were used.

414

is not easly to be computed

is difficult to be computed due to the fact

416

In this way the insufficiency of data for the estimation of the density functions would be covered and their calculation would be would be carried out

In this way, the lack of data for the estimation of the density functions would be solved and their calculation would be carried out

420

the set of variables based on in

the set of variables based on

432

is defined as

is defined as:

438

Assuming found the suboptimal set $S_{m−1}$ of $m−1$ variables,

Assuming the suboptimal set $S_{m−1}$ of $m−1$ variables to be found,

439

to add

to be added

443

thousand

thousands

446

Indicate that

It should be noted that

462

an Multi-Objective Optimization Evolutionary

a Multi-Objective Optimization Evolutionary

468

 is represented by a chromosome, and said chromosome is made up of different genes

 is represented by a chromosome, which is made up of different genes

479

 when said VOI is not used

 when that VOI is not used

490

The population size used in the simulation carried out was 250.

The population size that was used in the simulation was 250.

495

that have their value to one

that are set to one

496

elist strategy:

elitist strategy:

513

typically the maximum number of generations exceeded

typically, a maximum number of generations is reached

518

 (measured as the number of VOIs used )

 (measured as the number of needed VOIs).

524

like the one presented in the figure

like the one presented in Figure \ref{fig:Solution_ParetoFront}

530

a feature reduction is performed

a feature reduction procedure is performed

553

and test phase of the SVM classifier obtained

and a test phase of the obtained SVM classifier

558

potential solutions, called chromosome

i.e. potential solutions, called chromosomes

564

execution times

execution time

575

In multi-class problems is frequently used the confusion matrix

In multi-class problems the confusion matrix  is frequently used

591

the precision decreases

precision decreases

618

As was presented

As it was described

632

shows the location

show the location

637

It is relevant to make a comparison of the results in classification of PD disease

It is relevant to make a comparison of the PD disease classification results

642

Regions of the brain selected (Fig. 14-15)

Selected brain regions

644

The novel methodology presented

The novel presented methodology

645

classification of Parkinson's disease is of relevance to expert neurologists

classification of Parkinson's disease is of great relevance to expert neurologists

647

Obtaining the most relevant VOI was thanks to the implementation

Obtaining the most relevant VOIs was accomplished due to the implementation

677

The results obtained in the confusion matrices, for the different solutions of the MOE analyzed,

Results from the confusion matrices for the different solutions of the analyzed MOE