The Brain Tumor presents a highly critical situation concerning the brain, characterized by uncontrolled growth of an abnormal cell cluster. Early brain tumor detection is essential for accurate diagnosis and effective treatment planning. In this paper, novel Convolutional Neural Network (CNN) based Graph (GNN) model proposed using publicly available dataset from Kaggle to predict whether person has or not if yes then which type (Meningioma, Pituitary Glioma). objective research models...

In recent years, diabetes has become a global public health problem, and it is reported that the migrant Indians have more prevalence rate of Type-II diabetes. Also, type-II in are increased to large extent due modern lifestyle, food habits etc. this work, an ElectroGastroGram (EGG) based non-invasive assessment for early prediction proposed. Furthermore, EGG signals acquired from normal individuals people with age group between 50 65 who suffering using three electrode acquisition devices....

Mesenchymal stem cells (MSCs) have newly developed as a potential drug delivery system. MSC-based systems (MSCs-DDS) made significant strides in the treatment of several illnesses, shown by plethora research. However, this area research rapidly develops, issues with technique emerged, most often result its intrinsic limits. To increase effectiveness and security system, cutting-edge technologies are being concurrently. advancement MSC applicability clinical practice is severely hampered...

The development of deep learning algorithms in recent years has shown promise interpreting ECGs, as these can be trained on large datasets and learn to identify patterns associated with different heart conditions. advantage is their ability process amounts data quickly accurately, which help improve the speed accuracy diagnoses, especially for patients Our proposed work provides performant models based residual neural networks automate diagnosis 12-lead ECG signals more than 25 classes...

Ovarian cancer is a formidable health challenge that demands accurate and timely survival predictions to guide clinical interventions. Existing methods, while commendable, suffer from limitations in harnessing the temporal evolution of patient data capturing intricate interdependencies among different elements. In this paper, we present novel methodology which combines Temporal Analysis Graph Neural Networks (GNNs) significantly enhance ovarian rate predictions. The shortcomings current...

Biomedical image processing is finding useful in healthcare sector for the investigation, enhancement, and display of images gathered by distinct imaging technologies. Diabetic retinopathy (DR) an illness caused diabetes complications leads to irreversible injury retina blood vessels. Retinal vessel segmentation techniques are a basic element automated retinal disease screening system. In this view, study presents novel with deep learning based classification (BVS-DLC) model DR diagnosis...

Abstract The reconstruction of computed gastrointestinal tract tomography images has been a vibrant field study, particularly with the emergence deep learning techniques. These methods leverage data-driven models to enhance quality reconstructions. Our research delves into this domain by conducting comprehensive data challenge, where various algorithms were assessed using extensive public datasets. focal point was on quantitatively evaluating these methods. A noticeable outcome our...

Spinal cord segmentation is the process of identifying and delineating boundaries spinal in medical images such as magnetic resonance imaging (MRI) or computed tomography (CT) scans. This important for many applications, including diagnosis, treatment planning, monitoring injuries diseases. The involves using image processing techniques to identify differentiate it from other structures, vertebrae, cerebrospinal fluid, tumors. There are several approaches segmentation, manual by a trained...

Surveillance of pharmacovigilance, also known as drug safety surveillance, involves the monitoring and evaluation drug-related adverse events or side effects to ensure safe effective use medications. Pharmacovigilance is an essential component healthcare systems worldwide plays a crucial role in identifying managing concerns. Natural language processing (NLP) can play surveillance activities within pharmacovigilance by analyzing extracting information from various sources, such clinical...

Several computational and mathematical models of protein synthesis have been explored to accomplish the quantitative analysis components polysome structure. The effect gene sequence (coding non-coding region) in synthesis, mutation sequence, functional model ribosome needs be investigate relationship among further. Ribosomal computing is implemented by imitating property synthesis.

Clinical biomedical applications of genomic technologies are extensive and provide possibilities to enhance healthcare covering the span medical talents. Genome disorder prediction is an important issue in research. disorders cause multivariate diseases such as cancer, dementia, diabetes, Leigh syndrome, etc. Existing machine deep learning-based methods were introduced forecast genome disorders. However, outcomes not sufficient. To address this issue, propose a new method called Quadratic...

Background. Current medical care deeply relies on informatics during all stages of patient care, which is significantly enhanced due to its use. The healthcare professional’s formation in results crucial for their everyday practice. However, study programs not always provide education about the use this wide variety systems, and young professionals find that they need learn it over experience. aim was assess understanding dental students regarding ICTs. Materials Methods. A questionnaire...

Most of the dairy cows often have immune suppression during calving time and leads several metabolic disorders manifesting poorly functioning system. Hence, interaction between system metabolism is core important to read in terms benefit industries. In this, transition dry period lactation at most risk periods for cow’s body mechanism by this time, there are changes occur protein level. There been studies focused on casein its functions mammary glands. But few other proteins, which...

<title>Abstract</title> EEG signals are recordings of electrical activity in the brain, and they can be used to detect epileptic seizures. Cross-spectral analysis involves analyzing spectral coherence between different frequency bands signals. seizure detection is a technique seizures electroencephalography (EEG) by content signal bands. Spectral measure how correlated two domain, it identify patterns that characteristic Even if ECG, which provides direct heart rate, were polluted noise or...

BACKGROUND: The monitoring of fetal heart rate (FHR) before intrapartum has been crucial in modern obstetrics. FHR used for about 300 years to determine status, leading the development devices prevent death during gestation. While medical like electrocardiograms exist disease detection, their size and cost limit individual use. OBJECTIVE: To address cardiovascular issues pregnancy, a mobile system is developed display rates blood pressure on devices. generated from device with Bluetooth...

Abstract Background As health systems evolve, medical education needs to adapt programs that align with healthcare needs. Studies have shown integrating Health System Sciences (HSS) in the curriculum will empower future physicians additional skills provide system-based care within a system. Here, we describe process and content of integration HSS at one Saudi school. Methods This experience was conducted College Medicine Princess Nourah bint Abdulrahman University (PNU), Riyadh/Saudi Arabia....