hassaan malik - Academia.edu (original) (raw)

Papers by hassaan malik

Computers, Materials & Continua

Energies

The methods used in chemical engineering are strongly reliant on having a solid grasp of the ther... more The methods used in chemical engineering are strongly reliant on having a solid grasp of the thermodynamic features of complex systems. It is difficult to define the behavior of ions and molecules in complex systems and to make reliable predictions about the thermodynamic features of complex systems across a wide range. Deep learning (DL), which can provide explanations for intricate interactions that are beyond the scope of traditional mathematical functions, would appear to be an effective solution to this problem. In this brief Perspective, we provide an overview of DL and review several of its possible applications within the realm of chemical engineering. DL approaches to anticipate the molecular thermodynamic characteristics of a broad range of systems based on the data that are already available are also described, with numerous cases serving as illustrations.

Multimedia Tools and Applications

Coronavirus (COVID-19) has adversely harmed the healthcare system and economy throughout the worl... more Coronavirus (COVID-19) has adversely harmed the healthcare system and economy throughout the world. COVID-19 has similar symptoms as other chest disorders such as lung cancer (LC), pneumothorax, tuberculosis (TB), and pneumonia, which might mislead the clinical professionals in detecting a new variant of flu called coronavirus. This motivates us to design a model to classify multi-chest infections. A chest x-ray is the most ubiquitous disease diagnosis process in medical practice. As a result, chest x-ray examinations are the primary diagnostic tool for all of these chest infections. For the sake of saving human lives, paramedics and researchers are working tirelessly to establish a precise and reliable method for diagnosing the disease COVID-19 at an early stage. However, COVID-19's medical diagnosis is exceedingly idiosyncratic and varied. A multi-classification method based on the deep learning (DL) model is developed and tested in this work to automatically classify the COVID-19, LC, pneumothorax, TB, and pneumonia from chest x-ray images. COVID-19 and other chest tract disorders are diagnosed using a convolutional neural network (CNN) model called CDC Net that incorporates residual network thoughts and dilated convolution. For this study, we used this model in conjunction with publically available benchmark data to identify these diseases. For the first time, a single deep learning model has been used to diagnose five different chest ailments. In terms of classification accuracy, recall, precision, and f1-score, we compared the proposed model to three CNN-based pre-trained models, such as Vgg-19, ResNet-50, and inception v3. An AUC of 0.9953 was attained by the CDC Net when Multimedia Tools and Applications

Biomedical Engineering Advances

The dataset contains the DEXA scan images of spine infected due to osteoporosis . All images was ... more The dataset contains the DEXA scan images of spine infected due to osteoporosis . All images was obtained with the help Nishtar Medical Hospital, Multan Pakistan, from October 1, 2020 to December 9, 2020.

The dataset contains the chest radiographs of COVID-19 infected from Pakistan. All images was obt... more The dataset contains the chest radiographs of COVID-19 infected from Pakistan. All images was obtained from Government General Hospital Ghulam Muhammad Abad, Faisalabad, Pakistan, from April 15 to May 20,2020.

Computer Methods and Programs in Biomedicine, 2019

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service... more This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights  Proposed a residual structure with dilated convolution for the classification of pediatric pneumonia images.  Suggested an automated diagnostic algorithm for pediatric pneumonia to be used for end-to-end learning.  Efficiently solves the problem of low image resolution, partial occlusion and/or overlap in the inflammatory area of chest X-ray.  Used a transfer learning method to initialize model by weight parameters learned on large-scale datasets in the same field.  Effectively avoided negative impact of the introduction of structured noise on the performance of our model, and further improve the performance.

Multimedia Systems

Globally, coronavirus disease (COVID-19) has badly affected the medical system and economy. Somet... more Globally, coronavirus disease (COVID-19) has badly affected the medical system and economy. Sometimes, the deadly COVID-19 has the same symptoms as other chest diseases such as pneumonia and lungs cancer and can mislead the doctors in diagnosing coronavirus. Frontline doctors and researchers are working assiduously in finding the rapid and automatic process for the detection of COVID-19 at the initial stage, to save human lives. However, the clinical diagnosis of COVID-19 is highly subjective and variable. The objective of this study is to implement a multi-classification algorithm based on deep learning (DL) model for identifying the COVID-19, pneumonia, and lung cancer diseases from chest radiographs. In the present study, we have proposed a model with the combination of Vgg-19 and convolutional neural networks (CNN) named BDCNet and applied it on different publically available benchmark databases to diagnose the COVID-19 and other chest tract diseases. To the best of our knowledge, this is the first study to diagnose the three chest diseases in a single deep learning model. We also computed and compared the classification accuracy of our proposed model with four well-known pre-trained models such as ResNet-50, Vgg-16, Vgg-19, and inception v3. Our proposed model achieved an AUC of 0.9833 (with an accuracy of 99.10%, a recall of 98.31%, a precision of 99.9%, and an f1-score of 99.09%) in classifying the different chest diseases. Moreover, CNN-based pre-trained models VGG-16, VGG-19, ResNet-50, and Inception-v3 achieved an accuracy of classifying multi-diseases are 97.35%, 97.14%, 97.15%, and 95.10%, respectively. The results revealed that our proposed model produced a remarkable performance as compared to its competitor approaches, thus providing significant assistance to diagnostic radiographers and health experts.

2021 International Conference on Innovative Computing (ICIC)

In the modern era, deep learning studies have been undertaken in different fields of research suc... more In the modern era, deep learning studies have been undertaken in different fields of research such as speech recognition, image type, autonomous use, and language processing. The objective of the project is to examine the use of genomics in deep learning. The study focuses on literature using DL models. The in-depth study showed a significant improvement in overall performance in compound classification and regression problems, wherever the complicated form of large-dimensional statistics is difficult to exploit to take advantage of convolutional ML algorithms. In the field of biology, deep learning applications are gaining popularity in predicting the shape and feature of genomic elements, together with enhancers, promoters, or gene expression levels.. In this review article, we generally tend to expose the most used deep learning architectures for the genomic domain. Then we supplied a concise overview of deep learning applications in genomics and artificial biology on the ranges of DNA, RNA, and protein. Finally, we affirmed the prevailing difficult situations and emerging perspective of deep learning in genomics.

Proceedings of Engineering and Technology Innovation

Detecting cardiovascular disease (CVD) in the early stage is a difficult and crucial process. The... more Detecting cardiovascular disease (CVD) in the early stage is a difficult and crucial process. The objective of this study is to test the capability of machine learning (ML) methods for accurately diagnosing the CVD outcomes. For this study, the efficiency and effectiveness of four well renowned ML classifiers, i.e., support vector machine (SVM), logistics regression (LR), naive Bayes (NB), and decision tree (J48), are measured in terms of precision, sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC), correctly and incorrectly classified instances, and model building time. These ML classifiers are applied on publically available CVD dataset. In accordance with the measured result, J48 performs better than its competitor classifiers, providing significant assistance to the cardiologists.

International journal of engineering and technology, 2020

Cloud computing plays an important role in Information Technology (IT) management. Consequently, ... more Cloud computing plays an important role in Information Technology (IT) management. Consequently, various cloud computing developers and users experience different benefits and similarly challenges to its use and potential opportunities in driving the Fourth Industrial Revolution. Despite the increasing benefits of cloud computing, including increased speed of data processing and reduced costs compared to traditional computing, issues of security and privacy risk remain one of the greatest concerns in cloud computing. Through a systematic literature review, the evolution and developments in technology and issues of security and privacy from many years are examined to establish the trends in the threats; and thereby, provides a projection on the future of security of cloud computing. This paper presents the cloud computing aspects (types/aspects, and categories such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). The paper dwells o...

X-rays of wrist fracture collected from Al-huda Digital X-ray Laboratory, Nishtar Road, Multan, P... more X-rays of wrist fracture collected from Al-huda Digital X-ray Laboratory, Nishtar Road, Multan, Pakistan.

The purpose of this paper is to discuss how robots deal with unpredictable environment based on C... more The purpose of this paper is to discuss how robots deal with unpredictable environment based on CAD systems. Most of manufacturing companies use CAD packages. Robot programs are generating by using CAD drawing and these programs are commonly running on 3d CAD packages. By using 3d CAD package there is no expert skill is required to operate the robot programming. The 3d CAD packages are low cost and less time setup system. In this paper an experiment is discussed of robot programming that are generated from CAD drawing. In the end of this paper the overview of CAD related work is discussed.

Every one of us knows about the rise of Coronavirus (COVID-19) from Wuhan (China) and its effects... more Every one of us knows about the rise of Coronavirus (COVID-19) from Wuhan (China) and its effects into nearby states and further motherlands, increased domestic and worldwide methods are being occupied to contain the outburst. In terms of Economic and Social point of view, it directly disturbs the metropolitan markets on a high level by engaging all the capitals and towns in a lock-down situation. It’s also highlighted if this situation increases in different countries then it can lead in a direction to world-wide health disaster and in many accommodations as well. Be that as it may, while compelling conventions concerning the sharing of good information is underscored, urban information, then again, explicitly identifying with urban well-being and safe city ideas, is still seen from a patriot point of view as exclusively profiting a country's economy and its monetary and political impact. This article will explore the new and better universal understandings and also shows how s...

Deep learning methods have huge success in task specific feature representation. Transfer learnin... more Deep learning methods have huge success in task specific feature representation. Transfer learning algorithms are very much effective when large training data is scarce. It has been significantly used for diagnosis of diseases in medical imaging. This article presents a systematic literature review (SLR) by conducting a comparison of a variety of transfer learning approaches with healthcare experts in diagnosing diseases from medical imaging. This study has been compiled by reviewing research studies published in renowned venues between 2014 and 2019. Moreover, the data for the diagnosis performed by health care experts has also been acquired to perform a detailed comparative analysis for a wide range of diseases. The analysis has been performed on the basis of diseases, transfer learning approaches, type of medical imaging used. The comparative analysis is based on performance indices reported in studies which include diagnostic accuracy, true-positive (TP), false-positive (FP), tr...

The dataset contains the chest X-rays of COVID-19 pandemic infected patients from Pakistan. All i... more The dataset contains the chest X-rays of COVID-19 pandemic infected patients from Pakistan. All images was obtained with the help Government General Hospital Ghulam Muhammad Abad, Faisalabad, Pakistan, from April 1, 2020 to May 30,2020. All X-rays were captured from frontal view in jpeg format.