A5032727078- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- ECG Monitoring and Analysis
- Bioinformatics and Genomic Networks
- Heart Rate Variability and Autonomic Control
- Lung Cancer Diagnosis and Treatment
- Non-Invasive Vital Sign Monitoring
- EEG and Brain-Computer Interfaces
- Protein Structure and Dynamics
- Spectroscopy Techniques in Biomedical and Chemical Research
- Spectroscopy and Chemometric Analyses
- RNA and protein synthesis mechanisms
- Biomedical Text Mining and Ontologies
- RNA modifications and cancer
- Artificial Intelligence in Healthcare and Education
- Advanced Neural Network Applications
- Respiratory and Cough-Related Research
- Infrared Target Detection Methodologies
- Phonocardiography and Auscultation Techniques
- Topic Modeling
- User Authentication and Security Systems
- COVID-19 Digital Contact Tracing
Purdue University West Lafayette
2022-2025
Bangladesh University of Engineering and Technology
2018-2023
Qatar University
2022
The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems incapable to diagnose and test patients at the required rate. Given effects COVID-19 on pulmonary tissues, chest radiographic imaging become a necessity for screening monitoring disease. Numerous studies have proposed Deep Learning approaches automatic diagnosis COVID-19. Although these methods achieved outstanding performance in detection, they used limited X-ray (CXR) repositories evaluation, usually with...
Detecting COVID-19 at an early stage is essential to reduce the mortality risk of patients. In this study, a cascaded system proposed segment lung, detect, localize, and quantify infections from computed tomography images. An extensive set experiments were performed using Encoder–Decoder Convolutional Neural Networks (ED-CNNs), UNet, Feature Pyramid Network (FPN), with different backbone (encoder) structures variants DenseNet ResNet. The conducted for lung region segmentation showed Dice...
Cardiovascular diseases are one of the most severe causes mortality, annually taking a heavy toll on lives worldwide. Continuous monitoring blood pressure seems to be viable option, but this demands an invasive process, introducing several layers complexities and reliability concerns due non-invasive techniques not being accurate. This motivates us develop method estimate continuous arterial (ABP) waveform through approach using Photoplethysmogram (PPG) signals. We explore advantage deep...
RNA plays a crucial role not only in information transfer as messenger during gene expression but also various biological functions non-coding RNAs. Understanding mechanical mechanisms of function needs tertiary structure information; however, experimental determination three-dimensional structures is costly and time-consuming, leading to substantial gap between sequence structural data. To address this challenge, we developed NuFold, novel computational approach that leverages...
The coronavirus disease 2019 (COVID-19) has resulted in an ongoing pandemic worldwide. Countries have adopted non-pharmaceutical interventions (NPI) to slow down the spread. This study proposes agent-based model that simulates spread of COVID-19 among inhabitants a city. can be accommodated for any location by integrating parameters specific simulation gives number total cases. Considering each person as agent susceptible COVID-19, causes infected individuals transmit via various actions...
Cardiovascular diseases are the most common causes of death around world. To detect and treat heart-related diseases, continuous blood pressure (BP) monitoring along with many other parameters required. Several invasive non-invasive methods have been developed for this purpose. Most existing used in hospitals BP invasive. On contrary, cuff-based methods, which can predict systolic (SBP) diastolic (DBP), cannot be monitoring. studies attempted to from non-invasively collectible signals such...
Abstract Raman spectroscopy provides a vibrational profile of the molecules and thus can be used to uniquely identify different kinds materials. This sort molecule fingerprinting has led widespread application spectrum in various fields like medical diagnosis, forensics, mineralogy, bacteriology, virology, etc. Despite recent rise spectra data volume, there not been any significant effort developing generalized machine learning methods targeted toward analysis. We examine, experiment,...
A rapid and simple method was proposed for differentiation classification of eleven bacterial endotoxins based on surface enhanced Raman scattering (SERS) advanced machine learning algorithms.
Abstract The Coronavirus disease 2019 (COVID-19) has resulted in an ongoing pandemic worldwide. Countries have adopted Non-pharmaceutical Interventions (NPI) to slow down the spread. This study proposes Agent Based Model that simulates spread of COVID-19 among inhabitants a city. can be accommodated for any location by integrating parameters specific simulation gives number daily confirmed cases. Considering each person as agent susceptible COVID-19, model causes infected individuals...
The coronavirus disease 2019 (COVID-19) after outbreaking in Wuhan increasingly spread throughout the world. Fast, reliable, and easily accessible clinical assessment of severity can help allocating prioritizing resources to reduce mortality. objective study was develop validate an early scoring tool stratify risk death using readily available complete blood count (CBC) biomarkers. A retrospective conducted on twenty-three CBC biomarkers for predicting mortality 375 COVID-19 patients...
In recent years, physiological signal based authentication has shown great promises,for its inherent robustness against forgery. Electrocardiogram (ECG) signal, being the most widely studied biosignal, also received highest level of attention in this regard. It been proven with numerous studies that by analyzing ECG signals from different persons, it is possible to identify them, acceptable accuracy. work, we present, EDITH, a deep learning-based framework for biometrics system. Moreover,...
Problem—Since the outbreak of COVID-19 pandemic, mass testing has become essential to reduce spread virus. Several recent studies suggest that a significant number patients display no physical symptoms whatsoever. Therefore, it is unlikely these will undergo testing, which increases their chances unintentionally spreading Currently, primary diagnostic tool detect reverse-transcription polymerase chain reaction (RT-PCR) test from respiratory specimens suspected patient, invasive and...
Abstract Domains are functional and structural units of proteins that govern various biological functions performed by the proteins. Therefore, characterization domains in a protein can serve as proper representation Here, we employ self-supervised protocol to derive functionally consistent representations for learning domain-Gene Ontology (GO) co-occurrences associations. The domain embeddings constructed turned out be effective performing actual function prediction tasks. Extensive...
Cardiovascular diseases are one of the most severe causes mortality, taking a heavy toll lives annually throughout world. The continuous monitoring blood pressure seems to be viable option, but this demands an invasive process, bringing about several layers complexities. This motivates us develop method predict arterial (ABP) waveform through non-invasive approach using photoplethysmogram (PPG) signals. In addition we explore advantage deep learning as it would free from sticking ideally...
RNA is not only playing a core role in the central dogma as mRNA between DNA and protein, but also many non-coding RNAs have been discovered to unique diverse biological functions. As genome sequences become increasingly available our knowledge of grows, study RNA's structure function has more demanding. However, experimental determination three-dimensional structures both costly time-consuming, resulting substantial disparity sequence data structural insights. In response this challenge, we...
A Cyber-Physical System strongly depends on the sensor data to understand current condition of environment and act that.Due network faults, insufficient power supply, rough environment, become noisy system may perform unwanted operations causing severe damage.In this paper, a technique has been proposed analyze trustworthiness reading before performing operation based record.The employs regression analysis select nearby sensors develops linear model for target sensor.Using model, is...
Abstract Background Segmentation of nuclei in cervical cytology pap smear images is a crucial stage automated cancer screening. The task itself challenging due to the presence cells with spurious edges, overlapping cells, neutrophils, and artifacts. Methods After initial preprocessing steps adaptive thresholding, our approach, image passes through convolution filter out some noise. Then, contours from resultant are filtered by their distinctive contour properties followed nucleus size...