Biomedical Engineering Science and Technology
Second International Conference, ICBEST 2023, Raipur, India, February 10–11, 2023, Revised Selected Papers
Page
%P
30 Result(s)
within
Bikesh Kumar Singh
English
-
Article
Analysis of reading-task-based brain connectivity in dyslexic children using EEG signals
Developmental dyslexia, a neurodevelopment reading disorder, can impact even children with average intelligence. The present study examined the brain connectivity in dyslexic and control children during the re...
-
Article
Vocal tasks-based EEG and speech signal analysis in children with neurodevelopmental disorders: a multimodal investigation
Neurodevelopmental disorders (NDs) often hamper multiple functional prints of a child brain. Despite several studies on their neural and speech responses, multimodal researches on NDs are extremely rare. The p...
-
Article
Multicriteria decision support system for triage and ethical allocation of scarce resources to COVID-19 patients
Mitigating the rapid surge of Coronavirus disease (COVID-19) is one of the challenging tasks for the healthcare industry. While offering adequate healthcare services to the best of their ability, scarce medica...
-
Article
Type-2 diabetes identification from toe-photoplethysmography using Fourier decomposition method
Type-2 diabetes mellitus (DM-2) is a complicated endocrine and metabolism condition recognized as the most major non-communicable disease in the world. The complications associated with DM-2 involve cardiovasc...
-
Article
Multimodal classification of breast cancer using feature level fusion of mammogram and ultrasound images in machine learning paradigm
The manual examination of Breast Cancer (BC) images for disease detection is prone to error, is time-consuming, and has low accuracy. The Computer-Aided Detection (CAD) system can overcome the above-mentioned ...
-
Chapter and Conference Paper
EEG Based Classification of Learning Disability in Children Using Pretrained Network and Support Vector Machine
Learning disability (LD) is a commonly acknowledged neurological disorder that causes learners to struggle to decode, read, and write and in performing a mathematical task. If a child’s learning disabilities g...
-
Chapter and Conference Paper
A Two-Level Classifier for Prediction of Healthy and Unhealthy Lung Sounds Using Machine Learning and Convolutional Neural Network
The ability to detect lung disorders with the aid of lung sound auscultation has become very common these days. The early diagnose of these diseases can cause a reduced risk to loss of life. Auscultation has a...
-
Book and Conference Proceedings
-
Article
A hybrid bioinspired model for improving the efficiency of correlative auscultation analysis
Identification of lung health assists patients suffering from Asthma & Chronic Obstructive Pulmonary Disease (COPD) to take corrective measures. To perform this task, Computer Tomography (CT) scans, auscultati...
-
Article
Photoplethysmography signal-based automated diagnosis of type-2 diabetes using tunable-Q wavelet transform and least-square support vector machine classifier
Type-2 diabetes mellitus (T2DM) is a chronic metabolic disorder affecting numerous people throughout the world. If untreated in the initial stages, diabetes-related complications such as retinopathy, neuropath...
-
Article
A dual-modality evaluation of computer-aided breast lesion segmentation in mammogram and ultrasound using customized transfer learning approach
Manual segmentation of breast lesions is a tedious and time-consuming task. The existing state-of-the-art studies are evaluated on single modalities, i.e., either on mammogram or ultrasound thereby having limi...
-
Article
A real-time correlation model between lung sounds & clinical data for asthmatic patients
Lung sounds indicate the lung’s capacity to hold and breathe oxygen, which assists in evaluating its qualitative health. While clinical lung data like cough conditions, mucus levels, shortness of breath, wheez...
-
Chapter and Conference Paper
Beta Artificial Bee Colony Algorithm for EMG Feature Selection
The electromyography (EMG) signals play a very important role in the muscular activity of the human body. Muscular activities can be measured and analyzed through various movements such as writing, walking, ru...
-
Article
EEG based functional brain networks analysis in dyslexic children during arithmetic task
Developmental Dyslexia is a neuro-developmental disorder that often refers to a phonological processing deficit regardless of average IQ. The present study investigated the distinct functional changes in brain...
-
Article
Integrating patient symptoms, clinical readings, and radiologist feedback with computer-aided diagnosis system for detection of infectious pulmonary disease: a feasibility study
Automatic computer-aided diagnosis (CAD) system has been widely used as an assisting tool for mass screening and risk assessment of infectious pulmonary diseases (PDs). However, such a system still lacks clini...
-
Chapter and Conference Paper
Prediction of Hydroxyurea Effect on Sickle Cell Anemia Patients Using Machine Learning Method
The objective of this paper is to predict the effect of hydroxyurea of individuals suffering from Sickle Cell Disease (SCD) using predictive machine learning techniques. Nowadays worldwide sickle cell disease ...
-
Chapter and Conference Paper
Speech Parameter and Deep Learning Based Approach for the Detection of Parkinson’s Disease
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 e...
-
Chapter and Conference Paper
Hiding Patient Information in Medical Images: A Robust Watermarking Algorithm for Healthcare System
Electronically transmission of the medical images is an essential prerequisite in a Healthcare system. During transmission, the medical images can be hacked and altered either partially or in totality, unless ...
-
Chapter and Conference Paper
Feature Selection for Classification of Breast Cancer in Histopathology Images: A Comparative Investigation Using Wavelet-Based Color Features
Breast cancer is taken into account as one of the foremost common kinds of cancer occurring in women worldwide. This work is intended to develop an automated classification system in order to classify the brea...
-
Chapter and Conference Paper
Comparative Investigation of Different Classification Techniques for Epilepsy Detection Using EEG Signals
Among the major brain abnormalities that have been identified, various remedial strategies are proposed to tackle most of such conditions. One of the serious abnormalities of the nervous system is epilepsy, wh...
