Asifullah Khan
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View article: Data-driven strategies for drug repurposing: insights, recommendations, and case studies
Data-driven strategies for drug repurposing: insights, recommendations, and case studies Open
Drug discovery is a complex, time-intensive, and costly process, often requiring more than a decade and substantial financial investment to bring a single therapeutic to market. Drug repurposing, the systematic identification of new indica…
View article: DLRNA-BERTa: A transformer approach for RNA-drug binding affinity prediction
DLRNA-BERTa: A transformer approach for RNA-drug binding affinity prediction Open
RNA-based therapies are a rapidly expanding field, offering treatments for a wide range of diseases, including many rare conditions. To date, 24 RNA therapeutics have received FDA approval, with 131 more in clinical trials, underscoring RN…
View article: Data-driven strategies for drug repurposing: insights, recommendations, and case studies
Data-driven strategies for drug repurposing: insights, recommendations, and case studies Open
Drug discovery is a complex, time-intensive, and costly process, often requiring more than a decade and substantial financial investment to bring a single therapeutic to market. Drug repurposing, the systematic identification of new indica…
View article: Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention
Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention Open
Cancer is an abnormal growth with potential to invade locally and metastasize to distant organs. Accurate auto-segmentation of the tumor and surrounding normal tissues is required for radiotherapy treatment plan optimization. Recent AI-bas…
View article: Crime Hotspot Prediction Using Deep Graph Convolutional Networks
Crime Hotspot Prediction Using Deep Graph Convolutional Networks Open
Crime hotspot prediction is critical for ensuring urban safety and effective law enforcement, yet it remains challenging due to the complex spatial dependencies inherent in criminal activity. The previous approaches tended to use classical…
View article: AutoGen Driven Multi Agent Framework for Iterative Crime Data Analysis and Prediction
AutoGen Driven Multi Agent Framework for Iterative Crime Data Analysis and Prediction Open
This paper introduces LUCID-MA (Learning and Understanding Crime through Dialogue of Multiple Agents), an innovative AI powered framework where multiple AI agents collaboratively analyze and understand crime data. Our system that consists …
View article: MEAN VALUE OF THE ANGLE AMONG THE THREE VARIANTS OF ALATRAGUS LINE AND OCCLUSAL PLANE IN DENTATE SUBJECTS
MEAN VALUE OF THE ANGLE AMONG THE THREE VARIANTS OF ALATRAGUS LINE AND OCCLUSAL PLANE IN DENTATE SUBJECTS Open
Objectives: To determine the mean value of angle among the three variants of ala-tragus line (ATL) and OP in dentate individuals and to identify which among the three variants is parallel to OP.Materials and Methods: This descriptive cross…
View article: A Survey on Self-supervised Contrastive Learning for Multimodal Text-Image Analysis
A Survey on Self-supervised Contrastive Learning for Multimodal Text-Image Analysis Open
Self-supervised learning is a machine learning approach that generates implicit labels by learning underlined patterns and extracting discriminative features from unlabeled data without manual labelling. Contrastive learning introduces the…
View article: A Recent Survey of Vision Transformers for Medical Image Segmentation
A Recent Survey of Vision Transformers for Medical Image Segmentation Open
Medical image segmentation plays a crucial role in various healthcare applications, enabling accurate diagnosis, treatment planning, and disease monitoring. Convolutional Neural Networks (CNNs) have demonstrated exceptional performance in …
View article: Multi-Axis Vision Transformer for Medical Image Segmentation
Multi-Axis Vision Transformer for Medical Image Segmentation Open
View article: ISAnWin: inductive generalized zero-shot learning using deep CNN for malware detection across windows and android platforms
ISAnWin: inductive generalized zero-shot learning using deep CNN for malware detection across windows and android platforms Open
Effective malware detection is critical to safeguarding digital ecosystems from evolving cyber threats. However, the scarcity of labeled training data, particularly for cross-family malware detection, poses a significant challenge. This re…
View article: Early Detection and Classification of Apple Leaf Diseases Using Deep Learning Technique
Early Detection and Classification of Apple Leaf Diseases Using Deep Learning Technique Open
Apple leaf diseases represent a critical challenge for apple crop production, threatening both the quality and quantity of harvests. Leaves are essential to the growth and health of apple trees, as they play a pivotal role in photosynthesi…
View article: A Survey of the Self Supervised Learning Mechanisms for Vision Transformers
A Survey of the Self Supervised Learning Mechanisms for Vision Transformers Open
Advances in deep learning are re-defining how visual data is processed and understand by the machines. Vision Transformers (ViTs) have recently demonstrated prominent performance in computer vision related tasks. However, their performance…
View article: Channel Boosted CNN-Transformer-based Multi-Level and Multi-Scale Nuclei Segmentation
Channel Boosted CNN-Transformer-based Multi-Level and Multi-Scale Nuclei Segmentation Open
Accurate nuclei segmentation is an essential foundation for various applications in computational pathology, including cancer diagnosis and treatment planning. Even slight variations in nuclei representations can significantly impact these…
View article: Macroeconomic Indicators and Pakistan’s Banking Industry’s Shock Absorbing Capacity A Case Study of Conventional and Islamic Banks
Macroeconomic Indicators and Pakistan’s Banking Industry’s Shock Absorbing Capacity A Case Study of Conventional and Islamic Banks Open
The capacity of conventional and Islamic banks, operating in Pakistan, to absorb macroeconomic shocks is compared in this study. The study examines data from ten conventional and four Islamic banks from 2007Q1 to 2018Q4. The macroeconomic …
View article: Design and Performance Analysis of an Anti-Malware System Based on Generative Adversarial Network Framework
Design and Performance Analysis of an Anti-Malware System Based on Generative Adversarial Network Framework Open
The cyber realm is overwhelmed with dynamic malware that promptly penetrates all defense mechanisms, operates unapprehended to the user, and covertly causes damage to sensitive data. The current generation of cyber users is being victimize…
View article: A Recent Survey of Vision Transformers for Medical Image Segmentation
A Recent Survey of Vision Transformers for Medical Image Segmentation Open
Medical image segmentation plays a crucial role in various healthcare applications, enabling accurate diagnosis, treatment planning, and disease monitoring. Traditionally, convolutional neural networks (CNNs) dominated this domain, excelli…
View article: Lymphocyte detection for cancer analysis using a novel fusion block based channel boosted CNN
Lymphocyte detection for cancer analysis using a novel fusion block based channel boosted CNN Open
View article: SSMD-UNet: semi-supervised multi-task decoders network for diabetic retinopathy segmentation
SSMD-UNet: semi-supervised multi-task decoders network for diabetic retinopathy segmentation Open
Diabetic retinopathy (DR) is a diabetes complication that can cause vision loss among patients due to damage to blood vessels in the retina. Early retinal screening can avoid the severe consequences of DR and enable timely treatment. Nowad…
View article: A survey of the Vision Transformers and their CNN-Transformer based Variants
A survey of the Vision Transformers and their CNN-Transformer based Variants Open
Vision transformers have become popular as a possible substitute to convolutional neural networks (CNNs) for a variety of computer vision applications. These transformers, with their ability to focus on global relationships in images, offe…
View article: CB-HVTNet: A channel-boosted hybrid vision transformer network for lymphocyte assessment in histopathological images
CB-HVTNet: A channel-boosted hybrid vision transformer network for lymphocyte assessment in histopathological images Open
Transformers, due to their ability to learn long range dependencies, have overcome the shortcomings of convolutional neural networks (CNNs) for global perspective learning. Therefore, they have gained the focus of researchers for several v…
View article: MaxViT-UNet: Multi-Axis Attention for Medical Image Segmentation
MaxViT-UNet: Multi-Axis Attention for Medical Image Segmentation Open
Since their emergence, Convolutional Neural Networks (CNNs) have made significant strides in medical image analysis. However, the local nature of the convolution operator may pose a limitation for capturing global and long-range interactio…
View article: Comparison of Standalone and Hybrid Machine Learning Models for Prediction of Critical Heat Flux in Vertical Tubes
Comparison of Standalone and Hybrid Machine Learning Models for Prediction of Critical Heat Flux in Vertical Tubes Open
Critical heat flux (CHF) is an essential parameter that plays a significant role in ensuring the safety and economic efficiency of nuclear power facilities. It imposes design and operational restrictions on nuclear power plants due to safe…
View article: In Vitro Analysis of Cytotoxic Activities of Monotheca buxifolia Targeting WNT/β-Catenin Genes in Breast Cancer Cells
In Vitro Analysis of Cytotoxic Activities of Monotheca buxifolia Targeting WNT/β-Catenin Genes in Breast Cancer Cells Open
Breast cancer (BC) is known to be the most common malignancy among women throughout the world. Plant-derived natural products have been recognized as a great source of anticancer drugs. In this study, the efficacy and anticancer potential …
View article: Multi-Agent Reinforcement Learning for Traffic Flow Management of Autonomous Vehicles
Multi-Agent Reinforcement Learning for Traffic Flow Management of Autonomous Vehicles Open
Intelligent traffic management systems have become one of the main applications of Intelligent Transportation Systems (ITS). There is a growing interest in Reinforcement Learning (RL) based control methods in ITS applications such as auton…
View article: Deep Neural Networks based Meta-Learning for Network Intrusion Detection
Deep Neural Networks based Meta-Learning for Network Intrusion Detection Open
The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is dif…
View article: Early Risk Prediction of Chronic Myeloid Leukemia with Protein Sequences using Machine Learning-based Meta-Ensemble
Early Risk Prediction of Chronic Myeloid Leukemia with Protein Sequences using Machine Learning-based Meta-Ensemble Open
Leukemia, the cancer of blood cells, originates in the blood-forming cells of the bone marrow. In Chronic Myeloid Leukemia (CML) conditions, the cells partially become mature that look like normal white blood cells but do not resist infect…
View article: CB-HVT Net: A Channel-Boosted Hybrid Vision Transformer Network for Lymphocyte Detection in Histopathological Images
CB-HVT Net: A Channel-Boosted Hybrid Vision Transformer Network for Lymphocyte Detection in Histopathological Images Open
Detection of Tumor-Infiltrating Lymphocytes (TILs) has a high prognostic value in cancer diagnosis due to their ability to identify and kill cancer cells. However, this task is non-trivial due to their diverse morphology, overlapping bound…
View article: Detection of Data Scarce Malware Using One-Shot Learning With Relation Network
Detection of Data Scarce Malware Using One-Shot Learning With Relation Network Open
Malware has evolved to pose a major threat to information security. Efficient anti-malware software is essential in safeguarding confidential information from these threats. However, identifying malware continues to be a challenging task. …
View article: A Survey of the Recent Trends in Deep Learning Based Malware Detection
A Survey of the Recent Trends in Deep Learning Based Malware Detection Open
Monitoring Indicators of Compromise (IOC) leads to malware detection for identifying malicious activity. Malicious activities potentially lead to a system breach or data compromise. Various tools and anti-malware products exist for the det…