An Integrated Deep Learning and Belief Rule-Based Expert System for Visual Sentiment Analysis under Uncertainty

Zisad, Sharif Noor; Chowdhury, Etu; Hossain, Mohammad Shahadat; Islam, Raihan Ul; Andersson, Karl

doi:10.3390/a14070213

Cited by 19 publications

(5 citation statements)

References 34 publications

(41 reference statements)

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“…Moreover, this will make the diagnosis of PD more accurate and effective. A more efficient system can be built for PD detection using Belief Rule Based Expert Systems (BRBES) [10][11][12][13]25,34,37].…”

Section: Discussionmentioning

confidence: 99%

Early Detection of Parkinson’s Disease from Micrographic Static Hand Drawings

et al. 2021

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Parkinson's disease (PD) is a neurological illness that occurs by the degeneration of cells in the nervous system. Early symptoms include tremors or involuntary movements of the hands, arms, legs, and jaw. Currently, the only method to diagnose PD involves the observation of its prodromal symptoms. Moreover, detecting handwriting will work as a variable for clinitians to understand PD in patients better. With the advancement of technology, it is possible to build applications that will aid in diagnosing PD without any clinical intervention. The majority suffering from PD have handwriting abnormalities (referred to as micrographia), which is the most reported among earlier signs of the disease. So this research is undertaken by focusing on the implication of micrographia. For this purpose, handwritten images are collected from a group of 136 PD patients and 36 healthy patients. These images form a dataset of 800 images that are used to train a model which will accurately classify PD patients. To achieve this transfer learning is chosen because of its ability to produce accurate results regardless of the limited size of the dataset. Here, different models of transfer learning are trained to figure out the well-fitting model. It was observed that VGG-16 performed adequately with a training accuracy of 90.63% while a testing accuracy of 91.36%.

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Section: Discussionmentioning

confidence: 99%

Early Detection of Parkinson’s Disease from Micrographic Static Hand Drawings

et al. 2021

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“…The main aim of this research was to conduct a comparative analysis of various speech signal features for diagnosing Parkinson's disease using disjunctive BRBES [15,19,29] with optimization. It was observed that exploitive BRBaDE outperforms explorative BRBaDE, Genetic Algorithm and FMINCON in this task.…”

Section: Discussionmentioning

confidence: 99%

A Belief Rule Base Approach to Support Comparison of Digital Speech Signal Features for Parkinson’s Disease Diagnosis

et al. 2021

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Parkinson's disease is a neurological disorder. It affects the structures of the central and peripheral nervous system that control movement. One of the symptoms of Parkinson's disease is difficulty in speaking. Hence, analysis of speech signal of patients may provide valuable features for diagnosing. Previous works on diagnosis based on speech data have employed machine learning and deep learning techniques. However, these approaches do not address the various uncertainties in data. Belief rule based expert system (BRBES) is an approach that can reason under various forms of data uncertainty. Thus, the main objective of this research is to compare the potential of BRBES on various speech signal features of patients of parkinson's disease. The research took into account various types of standard speech signal features such MFCCs, TQWTs etc. A BRBES was trained on a dataset of 188 patients of parkinson's disease and 64 healthy candidates with 5fold cross validation. It was optimized using an exploitive version of the nature inspired optimization algorithm called BRB-based adaptive differential evolution (BRBaDE). The optimized model performed better than explorative BRBaDE, genetic algorithm and MATLAB's FMIN-CON optimization on most of these features. It was also found that for speech based diagnosis of Parkinson's disease under uncertainty, the features such as Glottis Quotient, Jitter variants, MFCCs, RPDE, DFA and PPE are relatively more suitable.

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“…The second method is to test the correlation of the data using the product moment and to determine the validity of the data using R table, while to test the consistency of the measuring instrument using cronbach alpha. The third method is the scientific method for solving problems by using the rule-based reasoning method [20], [21].…”

Section: Methodsmentioning

confidence: 99%

The new model for medicine distribution by combining of supply chain and expert system using rule-based reasoning method

Mufadhol

Mustafid²,

Jie³

et al. 2023

IJ-AI

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The medicine distribution supply chain is important, especially during the COVID-19 pandemic, because delays in medicine distribution can increase the risk for patients. So far, the distribution of medicines has been carried out exclusively and even some medicines are distributed on a limited basis because they require strict supervision from the Medicine Supervisory Agency in each department. However, the distribution of this medicine has a weakness if at one public Health center there is a shortage of certain types of medicines, it cannot ask directly to other public Health center, thus allowing the availability of medicines not to be fulfilled. An integrated process is needed that can accommodate regulations and leadership policies and can be used for logistics management that will be used in medicine distribution. This study will create a new model by combining supply chains with information systems and expert systems using the rule-based reasoning method as an inference engine that can be developed for medicine distribution based on a mobile hybrid system in the Demak District Health Office, Indonesia. So that a new framework model based on a mobile hybrid system can facilitate the distribution of medicines effectively and efficiently.

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An Integrated Deep Learning and Belief Rule-Based Expert System for Visual Sentiment Analysis under Uncertainty

Cited by 19 publications

References 34 publications

Early Detection of Parkinson’s Disease from Micrographic Static Hand Drawings

Early Detection of Parkinson’s Disease from Micrographic Static Hand Drawings

A Belief Rule Base Approach to Support Comparison of Digital Speech Signal Features for Parkinson’s Disease Diagnosis

The new model for medicine distribution by combining of supply chain and expert system using rule-based reasoning method

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