With the rapid advancements of ubiquitous information and communication technologies, a large number trustworthy online systems services have been deployed. However, cybersecurity threats are still mounting. An intrusion detection (ID) system can play significant role in detecting such security threats. Thus, developing an intelligent accurate ID is non-trivial research problem. Existing that typically used traditional network often fail cannot detect many known new threats, largely because...

In this paper <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> , we proposed an explainable deep neural networks (DNN)-based method for automatic detection of COVID-19 symptoms from chest radiography (CXR) images, which call 'DeepCOVIDExplainer'. We used 15,959 CXR images 15,854 patients, covering normal, pneumonia, and cases. are first comprehensively preprocessed augmented before classifying with a ensemble method, followed by...

Interference between pharmacological substances can cause serious medical injuries. Correctly predicting so-called drug-drug interactions (DDI) does not only reduce these cases but also result in a reduction of drug development cost. Presently, most drug-related knowledge is the clinical evaluations and post-marketing surveillance; resulting limited amount information. Existing data-driven prediction approaches for DDIs typically rely on single source information, while using information...

In recent years, as newer technologies have evolved around the healthcare ecosystem, more and data been generated. Advanced analytics could power collected from numerous sources, both institutions, or generated by individuals themselves via apps devices, lead to innovations in treatment diagnosis of diseases; improve care given patient; empower citizens participate decision-making process regarding their own health well-being. However, sensitive nature prohibits organizations sharing data....

Exponential growths of social media and micro-blogging sites not only provide platforms for empowering freedom expressions individual voices, but also enables people to express anti-social behavior like online harassment, cyberbul-lying, hate speech. Numerous works have been proposed utilize these data analysis, document characterization, sentiment analysis by predicting the contexts mostly highly resourced languages English. However, some are under-resources, e.g., South Asian Bengali,...

In this paper, we propose an explainable approach for hate speech detection from the under-resourced Bengali language, which called DeepHateExplainer. our approach, texts are first comprehensively preprocessed, before classifying them into political, personal, geopolitical, and religious hates using a neural ensemble method of transformer-based architectures (i.e., monolingual Bangla BERT-base, multilingual BERT-cased/uncased, XLM-RoBERTa). Subsequently, important (most least) terms...

Every day we experience unprecedented data growth from numerous sources, which contribute to big in terms of volume, velocity, and variability. These datasets again impose great challenges analytics framework computational resources, making the overall analysis difficult for extracting meaningful information a timely manner. Thus, harness these kinds challenges, developing an efficient is important research topic. Consequently, address by exploiting non-linear relationships very large...

Osteoarthritis (OA) is a degenerative joint disease, which significantly affects middle-aged and elderly people. Although primarily identified via hyaline cartilage change based on medical images, technical bottlenecks like noise, artifacts, modality impose an enormous challenge high-precision, objective, efficient early quantification of OA. Owing to recent advancements, approaches neural networks (DNNs) have shown outstanding success in this application domain. However, due nested...

Abstract Textile coloration is a complex process involving the interaction of dye molecules with fibers in bath. Synthetic dyes pose environmental hazards, leading to increased interest natural sourced from plants, animals, and minerals. However, often require mordants for application textiles. Despite their eco‐friendliness, can exhibit poor wash fastness on fabrics, necessitating further research enhance performance. This study investigates use mahogany sawdust extract as cotton...

Abstract An accurate diagnosis and prognosis for cancer are specific to patients with particular types molecular traits, which needs address carefully. The discovery of important biomarkers is becoming an step toward understanding the mechanisms carcinogenesis in genomics data clinical outcomes need be analyzed before making any decision. Copy number variations (CNVs) found associated risk individual cancers hence can used reveal genetic predispositions develops. In this paper, we collect...

Cancer is one of the deadliest diseases caused by abnormal behaviors genes that control cell division and growth. Genomics data clinical outcomes from multiplatform heterogeneous sources are used to make decisions for cancer patients, where both multimodality heterogeneity impose significant challenges bioinformatics tools algorithms. Numerous works have been proposed overcome these using sophisticated machine learning algorithms as either primary or supporting tools. In this paper, we...

Artificial intelligence (AI) systems are increasingly used in health and personalized care. However, the adoption of data-driven approaches many clinical settings has been hampered due to their inability perform a reliable safe manner leverage accurate trustworthy diagnoses. A critical challenging usage scenario for AI is aiding treatment cancerous conditions. Providing diagnosis cancer problem precision oncology. Although machine learning (ML)-based very effective at susceptibility...

Recently, a lectin was purified from the potato cultivated in Bangladesh locally known as Sheel. In present study cytotoxicity of against Ehrlich ascites carcinoma (EAC) cells studied by MTT assay vitro RPMI-1640 medium and 8.0-36.0 % cell growth inhibition observed at range 2.5-160 μg/ml protein concentration when incubated for 24 h. The lectin-induced apoptosis EAC confirmed fluorescence optical microscope. apoptotic death also using caspase inhibitors. Cells caused (36 %) remarkably...

AbstractMining combined association rules with correlation and market basket analysis can discover customer’s buying purchase along frequently correlated, associated-correlated, independent patterns synchronously which are extraordinarily useful for making everyday’s business decisions. However, due to the main memory bottleneck in single computing system, existing approaches fail handle big datasets. Moreover, most of them cannot overcome screenings overhead null transactions; hence,...

The discovery of important biomarkers is a significant step towards understanding the molecular mechanisms carcinogenesis; enabling accurate diagnosis for, and prognosis of, certain cancer type. Before recommending any diagnosis, genomics data such as gene expressions (GE) clinical outcomes need to be analyzed. However, complex nature, high dimensionality, heterogeneity in make overall analysis challenging. Convolutional neural networks (CNN) have shown tremendous success solving problems....

Mining interesting patterns from DNA sequences is one of the most challenging tasks in bioinformatics and computational biology. Maximal contiguous frequent are preferable for expressing function structure hence can capture common data characteristics among related sequences. Biologists interested finding orderly arrangements motifs that responsible similar expression a group genes. In order to reduce mining time complexity, however, existing sequence algorithms either focus on short or...

The study of genetic variants (GVs) can help find correlating population groups and to identify cohorts that are predisposed common diseases explain differences in disease susceptibility how patients react drugs. Machine learning techniques increasingly being applied interacting GVs understand their complex phenotypic traits. Since the performance a algorithm not only depends on size nature data but also quality underlying representation, deep neural networks (DNNs) learn non-linear mappings...