Brain tumors (BTs) are spreading very rapidly across the world. Every year, thousands of people die due to deadly brain tumors. Therefore, accurate detection and classification essential in treatment Numerous research techniques have been introduced for BT as well based on traditional machine learning (ML) deep (DL). The ML classifiers require hand-crafted features, which is time-consuming. On contrary, DL robust feature extraction has recently widely used purposes. this work, we propose a...

Cyberattacks can trigger power outages, military equipment problems, and breaches of confidential information, i.e., medical records could be stolen if they get into the wrong hands. Due to great monetary worth data it holds, banking industry is particularly at risk. As number digital footprints banks grows, so does attack surface that hackers exploit. This paper aims detect distributed denial-of-service (DDOS) attacks on financial organizations using Banking Dataset. In this research, we...

Breast cancer (BC) is a type of tumor that develops in the breast cells and one most common cancers women. Women are also at risk from BC, second life-threatening disease after lung cancer. The early diagnosis classification BC very important. Furthermore, manual detection time-consuming, laborious work, and, possibility pathologist errors, incorrect classification. To address above highlighted issues, this paper presents hybrid deep learning (CNN-GRU) model for automatic BC-IDC (+,−) using...

Early detection and proper treatment of epilepsy is essential meaningful to those who suffer from this disease. The adoption deep learning (DL) techniques for automated epileptic seizure using electroencephalography (EEG) signals has shown great potential in making the most appropriate fast medical decisions. However, DL algorithms have high computational complexity low accuracy with imbalanced data multi seizure-classification task. Motivated aforementioned challenges, we present a simple...

The Internet of Things (IoT) has emerged as a new technological world connecting billions devices. Despite providing several benefits, the heterogeneous nature and extensive connectivity devices make it target different cyberattacks that result in data breach financial loss. There is severe need to secure IoT environment from such attacks. In this paper, an SDN-enabled deep-learning-driven framework proposed for threats detection environment. state-of-the-art Cuda-deep neural network, gated...

Crop pests are to blame for significant economic, social, and environmental losses worldwide. Various have different control strategies, precisely identifying has become crucial pest is a difficulty in agriculture. Many agricultural professionals interested deep learning (DL) models since they shown promise image recognition. Pest identification approaches literature relatively low accuracy recognition classification due the complexity of their algorithms limited data availability....

Cancer has been found as a heterogeneous disease with various subtypes and aims to destroy the body’s normal cells abruptly. As result, it is essential detect prognosis distinct type of cancer since they may help survivors treatment in early stage. It must also divide patients into high- low-risk groups. While realizing efficient detection frequently time-taking exhausting task high possibility pathologist errors previous studies employed data mining machine learning (ML) techniques identify...

Object detection plays a vital role in the fields of computer vision, machine learning, and artificial intelligence applications (such as FUSE-AI (E-healthcare MRI scan), face detection, people counting, vehicle detection) to identify good defective food products. In field intelligence, target has been at its peak, but when it comes detecting multiple targets single image or video file, there are indeed challenges. This article focuses on improved K-nearest neighbor (MK-NN) algorithm for...

Nowadays, in a world full of uncertainties and the threat digital cyber-attacks, blockchain technology is one major critical developments playing vital role creative professional world. Along with energy, finance, governance, etc., healthcare sector most prominent areas where being used. We all are aware that data constitute our wealth currency; vulnerability security become even more significant point concern for healthcare. Recent cyberattacks have raised questions planning, requirement,...

The technological advancements of Internet Things (IoT) has revolutionized traditional Consumer Electronics (CE) into next-generation CE with higher connectivity and intelligence. This among sensors, actuators, appliances, other consumer devices enables improved data availability, provides automatic control in network. However, due to the diversity, decentralization, increase number traffic increased exponentially. Moreover, static network infrastructure-based approaches need manual...

Skin cancer is one of the widespread diseases among existing types. More importantly, detection lesions in early diagnosis has tremendously attracted researchers’ attention. Thus, artificial intelligence (AI)-based techniques have supported skin by investigating deep-learning-based convolutional neural networks (CNN). However, current methods remain challenging detecting melanoma dermoscopic images. Therefore, this paper, we propose an ensemble model that uses vision both EfficientNetV2S and...

The efficient patient-independent and interpretable framework for electroencephalogram (EEG) epileptic seizure detection (ESD) has informative challenges due to the complex pattern of EEG nature. Automated ES is crucial, Explainable Artificial Intelligence (XAI) urgently needed justify algorithmic predictions in clinical settings. Therefore, this study implements an XAI-based computer-aided system (XAI-CAESDs), comprising three major modules including feature engineering module, a...

Diabetic retinopathy (DR) is a worldwide problem associated with the human retina. It leads to minor and major blindness more prevalent among adults. Automated screening saves time of medical care specialists. In this work, we have used different deep learning (DL) based 3D convolutional neural network (3D‐CNN) architectures for binary multiclass (5 classes) classification DR. We considered mild, moderate, no, proliferate, severe DR categories. deployed two artificial data...

Recently, home automation system has getting significant attention because of the fast and advanced technology, making daily living more convenient. Almost everything been digitalized automated. The development will become easier popular use Internet Things (IoT). This paper described various interconnection systems actuators, sensors to enable multiple implementations. is known as HAS (Home system). It operates by connecting robust Application Programming Interface (API), which key a...

From a geological standpoint, northern Pakistan is one of the most active and unstable areas in world. As consequence, many massive landslides have occurred area historical times that destroyed infrastructure, blocked Hunza River, damaged Karakoram Highway repeatedly. However, despite high frequency large magnitude landslide events, consequent damages, entire largely understudied, mainly due to difficult logistics distances involved. This work aimed at applying potential use Interferometric...

Groundwater dynamics caused by extraction and recharge are one of the primary causes subsidence in urban environment. Lahore is second largest metropolitan city Pakistan. The rapid expansion this area due to high population density has increased demand for groundwater meet commercial household needs. Land inadequate long been a concern Lahore. This paper aims present persistent scatterer interferometry synthetic aperture radar (PS-InSAR) technique monitoring recent land Lahore, based on...

Early epileptic seizure prediction (ESP) has informative challenges due to the complexity of electroencephalogram (EEG) signals, patient variability, privacy, security issues regarding consumer health data, and on-time alarm triggers before an upcoming provide sufficient time for patients caregivers take appropriate action. Therefore, proposed study presents a novel patient-specific framework with Consumer Internet Things (CIoT) smart healthcare system anticipate onset seizures improve...

Epilepsy is a neurological disorder characterized by abnormal neuronal discharges that manifest in life-threatening seizures. These are often monitored via EEG signals, key aspect of biomedical signal processing (BSP). Accurate epileptic seizure (ES) detection significantly depends on the precise identification features, which requires deep understanding data's intrinsic domain. Therefore, this study presents an Advanced Multi-View Deep Feature Learning (AMV-DFL) framework based machine...

In the published article [...]

Lymphoedema is reported to occur in approximately one four women following curative treatment for breast cancer. Reported rates are almost exclusively level 1,2,3 axillary clearance with few data the current practice of 1,2 dissections. Swelling can affect whole upper limb but frequently will remain restricted hand, forearm or arm. The aims this study were determine incidence after dissection, degree and site swelling risk factors which might such incidences. Results available on 198...

Epilepsy is a common neurological condition. The effects of epilepsy are not restricted to seizures alone. They comprise wide spectrum problems that might impair and reduce quality life. Even with medication, 30% patients still have recurring seizures. An epileptic seizure caused by significant neuronal electrical activity, which affects brain activity. EEG shows these changes as high-amplitude spiky sluggish waves. Recognizing on an electroencephalogram (EEG) manually professional...