Rekh Ram Janghel

National Institute of Technology Raipur | NIT Raipur · Department of Information Technology

The healthcare sector is advancing with emerging technologies that help to detect new diseases or viruses worldwide. Generally, virus detection is based on various symptomatic tests and analysis of data samples that contain raw data (blood sample, protein sequence, etc.). Raw data cannot be directly processed by any machine learning (ML) technique....

Hyperspectral imaging is a crucial technology of remote sensing that captures hundreds of continuous spectral bands. In hyperspectral image (HSI) classification, pixels of HSI are classified into a particular class. HSI classification methods face challenges due to high dimensional data and the small number of labeled samples available. Recent year...

A Hyperspectral image (HSI) contains numerous spectral bands, providing better differentiation of ground objects. Although the data from HSI are very rich in information, their processing presents some difficulties in terms of computational effort and reduction of information redundancy. These difficulties stem mainly from the fact that the HSI con...

Linear-B cell epitopes (LBCE) play a vital role in vaccine design; thus, efficiently detecting them from protein sequences is of primary importance. These epitopes consist of amino acids arranged in continuous or discontinuous patterns. Vaccines employ attenuated viruses and purified antigens. LBCE stimulate humoral immunity in the body, where B an...

Prediction of conformational B-cell epitopes (CBCE) is an essential phase for vaccine design, drug invention, and accurate disease diagnosis. Many laboratorial and computational approaches have been developed to predict CBCE. However, laboratorial experiments are costly and time consuming, leading to the popularity of Machine Learning (ML)-based co...

Linear B-cell epitope (LBCE) identification is critical in developing peptide-based vaccines, antibody production, and immuno-diagnosis. Laboratory experiments are costly and time-consuming for this endeavour. Therefore, it is required to develop computational techniques to predict LBCE. Many techniques have been developed, but none of them achieve...

The ongoing growth of human society necessitates a massive increase in agricultural productivity. Plant diseases are the most significant factor in agriculture that influences the amount and quality of produced crops. There are other plant diseases, however, we'll concentrate on rice plant leaf disease. India produces a large number of rice harvest...

In India, over 25,000 people have died from cardiovascular annually over the past 4 years , and over 28,000 in the previous 3 years. Most of the deaths nowadays are mainly due to cardiovascular diseases (CVD). Arrhythmia is the leading cause of cardiovascular mortality. Arrhythmia is a condition in which the heartbeat is abnormally fast or slow. Th...

Rice is grown almost everywhere in the world, especially in Asian countries, because it is part of the diets of about half of the world's population. However, farmers and planting experts have faced several persistent agricultural obstacles for many years, including many rice diseases. Severe rice diseases might result in no grain harvest; hence, i...

Computer vision helps a computer to understand, classify and label images. Digital cameras can capture images and videos and then be analyzed with deep learning models for accurate identification and classification. Similarly, deep learning can be used for separating defective or unusable items for quality control. This paper presents a method to s...

According to World Health Organization, the main and primary reason for a large number of deaths globally is Arrhythmia. To reduce the number of deaths globally due to cardiovascular problems, the proper identification of CVDs is necessary and the patients should be provided with efficient treatment as quickly as possible. In this proposed study, i...

Crude oil price has a large influence on global environment and economy of the country. Similarly, gold price has also impact on economy and it reflects the economy strength of a country. So, the prediction of nonlinear oil and gold prices is the most prominent and arduous factor. In this work, Cluster-based Quasi oppositional based Crow Search Alg...

The application of compression of the data to digital files is called image compression. The encoding of images tackles the question of reducing the volume of data needed for digital image representation. The storage space for image loading is also limited. The compression of the picture can be lossy or lossless. This text aims to use different str...

Rice is the most consumed food for more than half the world. All over the world, approximately 15% of the rice get wasted because of leaf diseases. A computer-aided system needs a clear segmented lesion to detect such diseases, but blurriness, bad contrast, and dust particles on leaves are the challenge in proper segmentation and, further, for bett...

Epilepsy is a neurological disorder that affects the normal functioning of the brain. More than 10% of the population across the globe is affected by this disorder. Electroencephalogram (EEG) is prominently employed to accumulate information about the brain’s electrical activity. This study proposes an end-to-end system using a combination of two d...

Purpose Automated skin lesion analysis plays a vital role in early detection. Having relatively small-sized imbalanced skin lesion datasets impedes learning and dominates research in automated skin lesion analysis. The unavailability of adequate data poses difficulty in developing classification methods due to the skewed class distribution. Design...

Rice is amongst the majorly cultivated crops in India and its leaf diseases can have a substantial impact on output and quality. The most important component is identifying rice leaf diseases, which have a direct impact on the economy and food security. Brown spot, Leaf Blast, Hispa are the most frequently occurring rice leaf diseases. To resolve t...

The COVID-19 pandemic, probably one of the most widespread pandemics humanity has encountered in the twenty first century, caused death to almost 1.75 M people worldwide, impacting almost 80 M lives with direct contact. In order to contain the spread of coronavirus, it is necessary to develop a reliant and quick method to identify those who are aff...

The presence of artifacts limits the accuracy of detecting skin lesions. The current study presents an extensive appraisal of the impact of eight existing image-segmentation methods on the performance of 10 deep-learning-based models to detect and classify lesions. An empirical review was conducted using dual experimentation- with unsegmented origi...

The Hyperspectral Images (HSI) are now being widely popular due to the evolution of satellite imagery and camera technology. Remote sensing has also gained popularity and it is also closely related to HSI. HSI possesses a wide variety of spatial and spectral features. However, HSI also has a consider-able amount of useless or redundant data. This r...

Breast cancer is one of the primary causes of death that is occurred in females around the world. So, the recognition and categorization of initial phase breast cancer are necessary to help the patients to have suitable action. However, mammography images provide very low sensitivity and efficiency while detecting breast cancer. Moreover, Magnetic...

Pigmented skin lesion datasets comprise a higher percentage of benign lesion than the malignant lesions which lead to the class skewness issue in the dataset. Classifiers trained for analyzing the automated dermatoscopic pigmented lesions often suffer from data scarcity. Transfer learning permits to leverage the knowledge from the source domain to...

Epilepsy is a disease that is an electrophysiological disorder related to the brain and is characterized by various types of recurrent seizures. Electroencephalogram (EEG) is a test that is developed by various neurologists to capture the electrical signals that occur in the brain and is widely used for the Analysis and detection of epileptic seizu...

Stock index price forecasting is the influential indicator for investors and financial investigators by which decision making capability to achieve maximum benefit with minimum risk can be improved. So, a robust engine with capability to administer useful information is desired to achieve the success. The forecasting effectiveness of stock market i...

A computer-aided-diagnostic system for diagnosing melanoma often uses distinct kinds of features for characterizing the lesions. Extracting distinct features from melanocytic images represents the various characteristics of pigmented lesions. Concatenating such features distinguishes extracted feature's information effectively while eliminating the...

A correction to this paper has been published: https://doi.org/10.1007/s11063-021-10527-5

Alzheimer’s disease (AD) is a human brain disease that remains as a common cause of dementia, which occurs mainly in middle-aged or grown-up individuals. AD results in cognitive decline and memory loss. AD is caused by the decomposition of plaques around the nerves of brains or around the brain cells, where the brain cells get neurofibrillary tangl...

Stock price prediction is a significant index which helps to achieve maximum benefit with minimum risk by increasing the decision making capability of financial investigators and investors. However, the problem of short term stock price prediction is a complex task due to its uncertainty, discontinuity, and random nonlinear nature. In this paper, a...

Purpose:Less contrast between lesions and skin, blurriness, darkened lesion images, presence of bubbles, hairs are the artifactsmakes the issue challenging in timely and accurate diagnosis of melanoma. In addition, huge similarity amid nevus lesions and melanoma pose complexity in investigating the melanoma even for the expert dermatologists. Metho...

In this paper, we propose an effective electrocardiogram (ECG) signal classification method using XGBoost classifier. The ECG signals are passed through four phases of data acquisition, noise filtering, feature extraction, and classification. In first phase, dataset is collected from the MIT-BIH arrhythmia database. In second phase, noise is remove...

Symbiotic Organism Search (SOS) is a novel metaheuristic algorithm based on reciprocal behaviour of organisms in environment by considering three imperative relationships such as mutualism, commensalism and parasitism. The mutualism phase of SOS algorithm contemplates Benefit Factors (BFs) which influences the SOS algorithm. In this work, two novel...

Significant advances in deep learning techniques have made it possible to offer technologically advanced methods to detect cardiac abnormalities. In this study, we have proposed a new deep learning based Restricted Boltzmann machine (RBM) model for the classification of arrhythmias from Electrocardiogram (ECG) signal. The work is divided into three...

Parkinson’s disease is one of the common chronic and progressive neurodegenerative diseases across the globe. Speech parameters are the most important indicators that can be used to detect the disease at its early stage. In this article, an efficient approach using Convolutional Neural Network (CNN) is used to predict Parkinson’s disease by using s...

Low contrast images and blurriness pose challenge in the over‐segmentation of image, which increases model complexities. In this work, a novel hybrid dermoscopic skin‐lesion segmentation method, namely SLICACO, is proposed incorporating the simple linear iterative clustering (SLIC) and ant colony optimization (ACO) algorithms. The working of propos...

Epilepsy is one of the most common neurological brain dysfunctions after stroke, Alzheimer and migraine in humans. Epilepsy is a disease that affects approximately 50 million people worldwide. Seizure is occurred due to abnormal electrical discharges of the neurons in the brain cell. EEG is commonly used to accommodate information about the electri...

Alzheimer’s disease (AD) is the most common type of dementia. In all leading countries, it is one of the primary reasons of death in senior citizens. Currently, it is diagnosed by calculating the MSME score and by the manual study of MRI Scan. Also, different machine learning methods are utilized for automatic diagnosis, but existing has some limit...

Purpose According to the World Health Organization, arrhythmia is one of the primary causes of deaths across the globe. In order to reduce mortality rate, cardiovascular disease should be properly identified and the proper treatment for the same should be immediately provided to the patients. The objective of this paper was to implement a better he...

Early detection of cardiac arrhythmia is needed to reduce mortality. Automatically detecting the cardiac arrhythmias is a very challenging task. In this paper, a new deep convolutional encoded feature (CEF) based on non-linear compression composition is applied to diminish the ECG signal segment size. Bidirectional long short-term memory (BLSTM) ne...

Epilepsy is a neurological ailment that influence around 1% of mankind. Around 10% of the United States population experience at least a single convulsion in their life. Epilepsy is distinguished by the inclination of the brain to generate unexpected bursts of strange electrical action which disrupts the normal functioning of the brain. Generally p...

In a country like India where 16% of the total GDP growth is contributed by agriculture alone and majority of the people rely on it for their source of living, it is of utmost importance that the threats to the production of crops should be minimized. Crop leaf disease is major type of diseases suffered by crops; its manual identification is a diff...

Liver is one of the biggest gland and only organ of the human body which can restore harmed cells. Disorders in liver function affects food digestion and releasing of harmful toxic substances from the body which may results in severe liver diseases like jaundice, abdominal pain abdominal swelling, etc. These diseases require clinical care by expert...

Skin cancer is deemed as the lethal type of cancer threatening worldwide with an increase in mortality rate per year. The growing incidences of melanoma skin cancer have introduced numerous treatment options. However, surgical treatment remains the basis for treating skin cancers. Automated skin cancer detection still remains a challenging task in...

Purpose The purpose of this paper is to modify the crow search algorithm (CSA) to enhance both exploration and exploitation capability by including two novel approaches. The positions of the crows are updated in two approaches based on awareness probability (AP). With AP, the position of a crow is updated by considering its velocity, calculated in...

Purpose The study aims to cope with the problems confronted in the skin lesion datasets with less training data toward the classification of melanoma. The vital, challenging issue is the insufficiency of training data that occurred while classifying the lesions as melanoma and non-melanoma. Design/methodology/approach In this work, a transfer lear...

The high mortality rate that has been prevailing among cardiac patients can be reduced to some extent through early detection of the heart-related diseases which can be done with the help of automated computer-aided diagnosing machines. There is a need for an expert system that automatically detects the abnormalities in the heart rhythms. Various n...

Objectives Alzheimer's Disease (AD) is the most general type of dementia. In all leading countries, it is one of the primary reasons of death in senior citizens. Currently, it is diagnosed by calculating the MSME score and by the manual study of MRI Scan. Also, different machine learning methods are utilized for automatic diagnosis but existing has...

The report of World Health Organization (WHO) specifies that the diagnosis and treatment of cardiovascular diseases are challenging tasks. To study the electrical conductivity of the heart, Electrocardiogram (ECG) which is an inexpensive diagnostic tool, is used. Classification is the most well-known topic for arrhythmia detection related to cardio...

Electrocardiogram is a diagnostic tool that makes a record of the muscular and electrical activities of the heart for showing that data as a trace on a piece of paper, which is then carefully studied and interpreted by a clinical assistant. Classification of ECG signals on performance factors like sensitivity, specificity and accuracy using machine...

Alzheimer's is the most common form of dementia in India and it is one of the leading causes of death in the world. Currently it is diagnosed by calculating the MSME score and by manual study of MRI scan. In this chapter, the authors develop and compare different methods to diagnose and predict Alzheimer's disease by processing structural magnetic...

Arrhythmia is one of the major cause of deaths across the globe. Almost 17.9 million deaths are caused due to cardiovascular diseases. In order to reduce this much mortality rate, the cardiovascular disease should be properly identified and the proper treatment for the same should be immediately provided to the patients. In this study, a new ensemb...

Designing an automated system for the prior detection of melanoma in dermoscopic images can reduce the mortality rate, which has been raised due to skin cancer. Early diagnosis is thus pivotal to increase the survival rate and to prevent demolition caused due to cancer. The focus of this experiment is to develop a non-invasive digitized dermoscopic...

Electrocardiogram (ECG) signals are electrical signals generated corresponding to activity of heart. ECG signals are recorded and analysed to monitor heart condition. In initial raw form, ECG signals are contaminated with different types of noises. These noises may be electrode motion artefact noise, baseline wander noise and muscle noise also know...

Electrocardiogram (ECG) signals are electrical signals generated corresponding to activity of heart. ECG signals are recorded and analysed to monitor heart condition. In initial raw form, ECG signals are contaminated with different types of noises. These noises may be electrode motion artefact noise, baseline wander noise and muscle noise also know...

Alzheimer's Disease (AD) is the most common type of dementia. In all leading countries, it is one of the primary reasons of death in senior citizens. Currently, it is diagnosed by calculating the MSME score and by the manual study of MRI Scan. Also, different machine learning methods are utilized for automatic diagnosis but existing has some limita...

Timely prediction of cardiovascular diseases with the help of a computer-aided diagnosis system minimizes the mortality rate of cardiac disease patients. Cardiac arrhythmia detection is one of the most challenging tasks, because the variations of electrocardiogram(ECG) signal are very small, which cannot be detected by human eyes. In this study, an...

The concept of deep learning originates from artificial neural networks which has become a very popular research area during the past few decades. There are two main reasons for for the wide acceptance of deep learning. First one being the overfitting problem has been partially resolved with the advent of big data analytics techniques. The second p...

Epilepsy is a neurological affliction that in impact around 1% of humankind. Around 10% of the United States populace involvement with minimum a solitary convulsion in their activity. Epilepsy has recognized respectively tendency of the cerebrum outcomes unforeseen blasts of weird electrical action which disturbs the typical working of the mind. Si...

In the field of medical science, achieving accurate diagnosis of disease before its treatment is a significant obstacle. A lot of tests are available, which not only complicates the diagnostic process but also finds difficulty in deriving results. Therefore, computational diagnostic techniques must be introduced with the support of artificial intel...

Electrocardiogram (ECG) arrhythmia is referred to as a change in human heart rhythm, and it becomes either too slow or very large compared to normal heart rhythms. This may cause disease affecting cardiac. Early correct identification of arrhythmia is important in the detection of cardiac disease and getting the better treatment of a patient. Numer...

Speech is the vocalized form of communication used by humans and some animals. It is based upon the syntactic combination of items drawn from the lexicon. Each spoken word is created out of the phonetic combination of a limited set of vowel and consonant speech sound units (phonemes). Here, the authors propose a deep learning model used on tensor f...

Epilepsy is a brain ailment identified by unpredictable interruptions of normal brain activity. Around 1% of mankind experience epileptic seizures. Around 10% of the United States population experiences at least a single seizure in their life. Epilepsy is distinguished by the tendency of the brain to generate unexpected bursts of unusual electrical...

Alzheimer's is the most common form of dementia in India and it is one of the leading causes of death in the world. Currently it is diagnosed by calculating the MSME score and by manual study of MRI scan. In this chapter, the authors develop and compare different methods to diagnose and predict Alzheimer's disease by processing structural magnetic...

Parkinson’s disease is a widespread disease among elder population worldwide caused by dopamine loss, which reduces quality of life because of motor and non-motor complications. In the current paper, nine soft computing models, i.e., Cubist, Cubist Committees, Random Forests, Kernel Support Vector Machine, Linear Regression, Naïve Bayes, Artificial...

Each year major part of a country’s wealth is spent on public health. The government organizations keep daily records of large volumes of public health-related data resulting in voluminous multivariate dataset. These datasets are spatially varying which poses a challenge for proper analysis. These datasets cannot be ignored since these are potentia...

Parkinson’s disease is a widespread disease among elder population worldwide effecting approximately 6.3 million people across all genders, races and cultures. It is caused by dopamine loss, a chemical mediator that is responsible for body’s ability to control the movements. The disease reduces quality of life because of motor and non-motor com...

Missing information are the general issue in healthcare examination framework and very much controlled investigation. Missing information produces one-sided estimation and diminishes the factual capability of an investigation, which prompts invalid outcomes. In this paper, we survey the sorts of traceless and method of missing information alongside...

Development of efficient, prompt and robust systems that are intelligent enough to replace/reduce human supervision in medical diagnosis is one of the primary objectives that have driven advancements in research for long. One area where this need for intelligent automation has been most acutely felt is related to the diagnosis of breast cancer in w...

A major problem in medical science is attaining the correct diagnosis of disease in precedence of its treatment. For the ultimate diagnosis, many tests are generally involved. Too many tests could complicate the main diagnosis process so that even the medical experts might have difficulty in obtaining the end results from those tests. A well-design...

In the present work an attempt is made to develop an intelligent Decision support system (IDSS) using the pathological attributes to predict the fetal delivery to be done normal or by surgical procedure. The pathological tests like Blood Sugar (BR), Blood pressure (BP), Resistivity Index (RI) and systolic / Diastolic (S/P) ratio will be recorded at...

In this paper a new approach for the prediction of breast cancer has been made by reducing the features of the data set using PCA (principal component analysis) technique and prediction results by simulating different models namely SANE (Symbiotic, Adaptive Neuro-evolution), Modular neural network, Fixed architecture evolutionary neural network (F-...

Breast cancer is one of the major causes of death in women which accounts one out of eight. As primary cause is still unknown, early detection increases better treatment and improves total recovery. We present some novel hybrid approaches for classification of breast cancer. Artificial Neural Network (ANN) which suffers credit assignment problem ca...

We construct a mixture of experts model for medical diagnosis. Each of the experts is a complex modular neural network. The first modularity clusters the entire input space into a set of modules. The second modularity divides the number of attributes. Each cluster is a neural network that solves the problem. The individual neural networks are evolv...

In the present work an attempt is made to develop an intelligent Decision support system (IDSS) using the pathological attributes to predict the fetal delivery to be done normal or by surgical procedure. The pathological tests like Blood Sugar (BR), Blood pressure (BP), Resistivity Index (RI) and systolic / Diastolic (S/P) ratio will be recorded at...

Breast cancer is the second leading cause of cancer deaths in women worldwide and occurs in nearly one out of eight women. In this paper we develop a hybrid intelligent system for diagnosis, prognosis and prediction for breast cancer using SANE (Symbiotic, Adaptive Neuro-evolution) and compare with ensemble ANN, modular neural network, fixed archit...