Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid gland.Accurate timely diagnosis of these is crucial for effective treatment patient care.This research introduces comprehensive approach to improve accuracy disorder through integration ensemble stacking advanced feature selection techniques.Sequential forward selection, sequential backward elimination, bidirectional...

As corona virus disease (COVID-19) is still an ongoing global outbreak, countries around the world continue to take precautions and measures control spread of pandemic. Because excessive number infected patients resulting deficiency testing kits in hospitals, a rapid, reliable, automatic detection COVID-19 extreme need curb infections. By analyzing chest X-ray images, novel metaheuristic approach proposed based on hybrid dipper throated particle swarm optimizers. The lung region was...

Breast cancer, which attacks the glandular epithelium of breast, is second most common kind cancer in women after lung and it affects a significant number people worldwide. Based on advantages Residual Convolutional Network Transformer Encoder with Multiple Layer Perceptron (MLP), this study proposes novel hybrid deep learning Computer-Aided Diagnosis (CAD) system for breast lesions. While backbone residual network employed to create features, transformer utilized classify according...

Acute lymphoblastic leukemia (ALL) is a deadly cancer characterized by aberrant accumulation of immature lymphocytes in the blood or bone marrow. Effective treatment ALL strongly associated with early diagnosis disease. Current practice for initial performed through manual evaluation stained smear microscopy images, which time-consuming and error-prone process. Deep learning-based human-centric biomedical has recently emerged as powerful tool assisting physicians making medical decisions....

One of the most promising research areas in healthcare industry and scientific community is focusing on AI-based applications for real medical challenges such as building computer-aided diagnosis (CAD) systems breast cancer. Transfer learning one recent emerging techniques that allow rapid progress improve imaging performance. Although deep classification cancer has been widely covered, certain obstacles still remain to investigate independency among extracted high-level features. This work...

With the help of machine learning, many problems that have plagued mammography in past been solved. Effective prediction models need normal and tumor samples. For medical applications such as breast cancer diagnosis framework, it is difficult to gather labeled training data construct effective learning frameworks. Transfer an emerging strategy has recently used tackle scarcity by transferring pre-trained convolutional network knowledge into domain. Despite well reputation transfer based on...

Human pose and gesture estimation are crucial in correcting physiotherapy fitness exercises. In recent years, advancements computer vision machine learning approaches have led to the development of sophisticated models that accurately track analyze human movements real time. This technology enables physiotherapists trainers gain valuable insights into their client's exercise forms techniques, facilitating more effective corrections personalized training regimens. research aims propose an...

The domestication of animals and the cultivation crops have been essential to human development throughout history, with agricultural sector playing a pivotal role. Insufficient nutrition often leads plant diseases, such as those affecting rice crops, resulting in yield losses 20-40% total production. These carry significant global economic consequences. Timely disease diagnosis is critical for implementing effective treatments mitigating financial losses. However, despite technological...

Pomegranates are nutrient-rich fruits renowned for their vibrant ruby-red seeds and antioxidant properties. With a rich history rooted in various cultures, pomegranates have gained widespread popularity distinct flavor potential health benefits. Timely detection understanding of the growth stages can facilitate optimized resource allocation, targeted interventions, efficient crop management. Additionally, early contributes to maximizing yield, ensuring product quality, mitigating risks such...

The increasing prevalence of mental disorders among youth worldwide is one society's most pressing issues. proposed methodology introduces an artificial intelligence-based approach for comprehending and analyzing the neurological disorders. This work draws upon analysis Cities Health Initiative dataset. It employs advanced machine learning deep techniques, integrated with data science, statistics, optimization, mathematical modeling, to correlate various lifestyle environmental factors...

This study proposes an advanced method for plant disease detection utilizing a modified depthwise convolutional neural network (CNN) integrated with squeeze-and-excitation (SE) blocks and improved residual skip connections. In light of increasing global challenges related to food security sustainable agriculture, this research focuses on developing highly efficient accurate automated system identifying diseases, thereby contributing enhanced crop protection yield optimization. The proposed...

Brain tumors (BTs) are deadly diseases that can strike people of every age, all over the world. Every year, thousands die brain tumors. Brain-related diagnoses require caution, and even smallest error in diagnosis have negative repercussions. Medical errors tumor common frequently result higher patient mortality rates. Magnetic resonance imaging (MRI) is widely used for evaluation detection. However, MRI generates large amounts data, making manual segmentation difficult laborious work,...

It is an undeniable fact that people excessively rely on social media for effective communication. However, there no appropriate barrier as to who becomes a part of the Therefore, unknown ruin fundamental purpose communication with irrelevant—and sometimes aggressive—messages. As its popularity increases, impact society also from primarily being positive negative. Cyber aggression negative impact; it defined willful use information technology harm, threaten, slander, defame, or harass...

Blood cells carry important information that can be used to represent a person's current state of health. The identification different types blood in timely and precise manner is essential cutting the infection risks people face on daily basis. BCNet an artificial intelligence (AI)-based deep learning (DL) framework was proposed based capability transfer with convolutional neural network rapidly automatically identify eight-class scenario: Basophil, Eosinophil, Erythroblast, Immature...

The rapid population growth results in a crucial problem the early detection of diseases medical research. Among all cancers unveiled, breast cancer is considered second most severe cancer. Consequently, an exponential rising death cases incurred by expected due to and lack resources required for performing diagnoses. Utilizing recent advances machine learning could help staff diagnosing as they offer effective, reliable, responses, which decreasing risk. In this paper, we propose new...

Nowadays global market products are readily accessible worldwide, and a vast array of reviews across numerous platforms posted daily in several categories, making it challenging for customers to stay informed about their product interests. To make decisions regarding quality, users require access ratings. Owners managers must analyze customer ratings the underlying emotional content enhance product's cost, service, environmental impact. The primary aim our proposed research is accurately...

Introduction Acute heart failure (AHF) is a serious medical problem that necessitates hospitalization and often results in death. Patients hospitalized the emergency department (ED) should therefore receive an immediate diagnosis treatment. Unfortunately, there not yet fast accurate laboratory test for identifying AHF. The purpose of this research to apply principles explainable artificial intelligence (XAI) analysis hematological indicators Methods In retrospective analysis, 425 patients...

In this paper, an enhanced version of the Exponential Distribution Optimizer (EDO) called mEDO is introduced to tackle global optimization and multi-level image segmentation problems. EDO a math-inspired optimizer that has many limitations in handling complex multi-modal tries solve these drawbacks using 2 operators: phasor operator for diversity enhancement adaptive p-best mutation strategy preventing it converging local optima. To validate effectiveness suggested optimizer, comprehensive...

Diabetic Maculopathy (DM) is considered the most common cause of permanent visual impairment in diabetic patients. The absence clear pathological symptoms DM hinders timely diagnosis and treatment such a critical condition. Early feasible through eye screening technologies. However, manual inspection retinography images by specialists time-consuming routine. Therefore, many deep learning-based computer-aided systems have been recently developed for automatic prognosis retinal images. Manual...