Bone scintigraphy based on deep learning model and modified growth optimizer.

Bone scintigraphy is recognized as an efficient diagnostic method for whole-body screening for bone metastases. At the moment, whole-body bone scan image analysis is primarily dependent on manual reading by nuclear medicine doctors. However, manual analysis needs substantial experience and is both stressful and time-consuming.

Noise filter using a periodic system of dual Helmholtz resonators.

This study investigates noise reduction using a periodic arrangement of dual Helmholtz resonators and explores the introduction of defects within this periodic structure. The transfer matrix method was employed to carry out theoretical research. The computations of the interface response function approach results are verified, and consistent outcomes are demonstrated.

A non-invasive AI-based system for precise grading of anosmia in COVID-19 using neuroimaging.

COVID-19 (Coronavirus), an acute respiratory disorder, is caused by SARS-CoV-2 (coronavirus severe acute respiratory syndrome). The high prevalence of COVID-19 infection has drawn attention to a frequent illness symptom: olfactory and gustatory dysfunction. The primary purpose of this manuscript is to create a Computer-Assisted Diagnostic (CAD) system to determine whether a COVID-19 patient has normal, mild, or severe anosmia.

Analyzing invariants and employing successive reductions for the extended Kadomtsev Petviashvili equation in (3+1) dimensions.

In this research, we employ the potent technique of Lie group analysis to derive analytical solutions for the (3+1)-extended Kadomtsev-Petviashvili (3D-EKP) equation. The systematic application of this method enables the identification of Lie point symmetries associated with the equation, leading to the derivation of an optimal system of one-dimensional subalgebras relevant to the equation. This optimal system is utilized to obtain several invariant solutions.

AI-based model for automatic identification of multiple sclerosis based on enhanced sea-horse optimizer and MRI scans.

This study aims to develop an AI-enhanced methodology for the expedited and accurate diagnosis of Multiple Sclerosis (MS), a chronic disease affecting the central nervous system leading to progressive impairment. Traditional diagnostic methods are slow and require substantial expertise, underscoring the need for innovative solutions. Our approach involves two phases: initially, extracting features from brain MRI images using first-order histograms, the gray level co-occurrence matrix, and local binary patterns.

Dynamics of invariant solutions of the DNA model using Lie symmetry approach.

The utilization of the Lie group method serves to encapsulate a diverse array of wave structures. This method, established as a robust and reliable mathematical technique, is instrumental in deriving precise solutions for nonlinear partial differential equations (NPDEs) across a spectrum of domains. Its applications span various scientific disciplines, including mathematical physics, nonlinear dynamics, oceanography, engineering sciences, and several others.

Cardiac Fibrosis Automated Diagnosis Based on FibrosisNet Network Using CMR Ischemic Cardiomyopathy.

Ischemic heart condition is one of the most prevalent causes of death that can be treated more effectively and lead to fewer fatalities if identified early. Heart muscle fibrosis affects the diastolic and systolic function of the heart and is linked to unfavorable cardiovascular outcomes. Cardiac magnetic resonance (CMR) scarring, a risk factor for ischemic heart disease, may be accurately identified by magnetic resonance imaging (MRI) to recognize fibrosis.

Dynamical behavior of solitons of the (2+1)-dimensional Konopelchenko Dubrovsky system.

Utilizing nonlinear evolution equations (NEEs) is common practice to establish the fundamental assumptions underlying natural phenomena. This paper examines the weakly dispersed non-linear waves in mathematical physics represented by the Konopelchenko-Dubrovsky (KD) equations. The [Formula: see text]-expansion method is used to analyze the model under consideration.

Elemental distribution patterns in rock samples from Egypt using neutron activation and complementary X-ray fluorescence analyses.

The study utilized instrumental neutron activation analysis (INAA) and X-ray fluorescence (XRF) to accurately analyze the elemental composition of 28 felsite (rhyolite), rock samples. Statistical approaches, including bivariate and multivariate analysis, were employed to characterize the rocks and determine their origin. Major findings include significantly high levels of silicon (297000 ± 4000) mg/kg and low levels were noticed for gold (0.

Numerical study of unsteady tangent hyperbolic fuzzy hybrid nanofluid over an exponentially stretching surface.

The significance of fuzzy volume percentage on the unsteady flow of MHD tangent hyperbolic fuzzy hybrid nanofluid towards an exponentially stretched surface is scrutinized. The heat transport mechanism is classified by Joule heating, nonlinear thermal radiation, boundary slippage, and convective circumstances. Ethylene glycol (EG) as a host fluid along with the nanomaterial's Cu and [Formula: see text] are used for heat transfer analysis is also considered in this investigation.

Bone metastasis detection method based on improving golden jackal optimization using whale optimization algorithm.

This paper presents a machine learning-based technique for interpreting bone scintigraphy images, focusing on feature extraction and introducing a new feature selection method called GJOW. GJOW enhances the effectiveness of the golden jackal optimization (GJO) algorithm by integrating operators from the whale optimization algorithm (WOA). The technique's performance is evaluated through extensive experiments using 18 benchmark datasets and 581 bone scan images obtained from a gamma camera, including 362 abnormal and 219 normal cases.

Early Melanoma Detection Based on a Hybrid YOLOv5 and ResNet Technique.

Skin cancer, specifically melanoma, is a serious health issue that arises from the melanocytes, the cells that produce melanin, the pigment responsible for skin color. With skin cancer on the rise, the timely identification of skin lesions is crucial for effective treatment. However, the similarity between some skin lesions can result in misclassification, which is a significant problem.

Numerical investigation of dusty tri-hybrid Ellis rotating nanofluid flow and thermal transportation over a stretchable Riga plate.

Due to high-ultra thermic significances, the nanosize materials are used in various chemical and mechanical engineering, modern technology and thermic engineering eras. For industrial growth of a country, one of the biggest challenges for engineers and scientists is improvement in thermal production and resources. In this study we analyzed the momentum and thermic aspects of MHD Ellis ternary nano material embedded with dust particles via stretchable Riga plate including volume concentration of dust material.

Mixed convection and activation energy impacts on MHD bioconvective flow of nanofluid with irreversibility assessment.

In this communication irreversibility minimization in bio convective Walter's-B nanofluid flow by stretching sheet is studied. Suspended nanoparticles in Walter's-B fluid are stabilized by utilizing microorganisms. Total irreversibility is obtained via thermodynamics second law.

Refined Automatic Brain Tumor Classification Using Hybrid Convolutional Neural Networks for MRI Scans.

Refined hybrid convolutional neural networks are proposed in this work for classifying brain tumor classes based on MRI scans. A dataset of 2880 T1-weighted contrast-enhanced MRI brain scans are used. The dataset contains three main classes of brain tumors: gliomas, meningiomas, and pituitary tumors, as well as a class of no tumors.

Detection of Diabetic Retinopathy Using Extracted 3D Features from OCT Images.

Diabetic retinopathy (DR) is a major health problem that can lead to vision loss if not treated early. In this study, a three-step system for DR detection utilizing optical coherence tomography (OCT) is presented. First, the proposed system segments the retinal layers from the input OCT images.

Role of Imaging and AI in the Evaluation of COVID-19 Infection: A Comprehensive Survey.

Coronavirus disease 2019 (COVID-19) is a respiratory illness that started and rapidly became the pandemic of the century, as the number of people infected with it globally exceeded 253.4 million. Since the beginning of the pandemic of COVID-19, over two years have passed.

Williamson magneto nanofluid flow over partially slip and convective cylinder with thermal radiation and variable conductivity.

This article is concerned with the study of MHD non-Newtonian nanofluid flow over a stretching/shrinking cylinder along with thermal radiation effects. Two-component slip mechanism models, namely Brownian motion and thermophoresis of nanofluid for the mass and energy transportation, developed by Buongiorno, are used. Convective heat transfer and nonuniform magnetic field are retained for the expanding/contracting cylinder.

Investigation of the Near-Tip Stress Field of a Notch Terminating at a Bi-Material Interface.

The article deals with the problem of a sharp corner, the tip of which is located on the bi-material interface. The paper presents a qualitative and quantitative description of singular stress fields occurring in the tip area of such a stress concentrator. The qualitative description was obtained by solving the problem of the plane theory of elasticity with appropriately defined boundary conditions.

An experimental investigation of head loss through a triangular "V- shaped" screen.

Common traditional screens (screens perpendicular and vertical to the flow direction) face extensive problems with screen blockage, which can result in adverse hydraulic, environmental, and economic consequences. Experimentally, this paper presents an advanced trash screen concept to reduce traditional screen problems and improve the hydraulic performance of screens. The traditional screen is re-developed using a triangular V shape with circular bars in the flow direction.