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...

Cardiovascular diseases remain one of the main threats to human health, significantly affecting quality and life expectancy. Effective prompt recognition these is crucial. This research aims develop an effective novel hybrid method for automatically detecting dangerous arrhythmias based on cardiac patients’ short electrocardiogram (ECG) fragments. study suggests using a continuous wavelet transform (CWT) convert ECG signals into images (scalograms) examining task categorizing 2-s segments...

Concerning the oversight and safeguarding of aquatic environments, it is necessary to ascertain quantity fish, their size, distribution. Many deep learning (DL), artificial intelligence (AI), machine (ML) techniques have been developed oversee safeguard fish species. Still, all previous work had some limitations, such as a limited dataset, only binary class categorization, employing one technique (ML/DL), etc. Therefore, in proposed work, authors develop an architecture that will eliminate...

The Internet of Medical Things (IoMT) has revolutionized healthcare with remote patient monitoring and real-time diagnosis, but securing data remains a critical challenge due to sophisticated cyber threats the sensitivity medical information. Traditional machine learning methods struggle capture complex patterns in IoMT data, conventional intrusion detection systems often fail identify unknown attacks, leading high false positive rates compromised security. To address these issues, we...

Breast cancer (BC) is a malignant neoplasm that originates in the mammary gland's cellular structures and remains one of most prevalent cancers among women, ranking second cancer-related mortality after lung cancer. Early accurate diagnosis crucial due to heterogeneous nature breast its rapid progression. However, manual detection classification are often time-consuming prone errors, necessitating development automated reliable diagnostic approaches. Recent advancements deep learning have...

A brain tumor is a serious medical condition characterized by the abnormal growth of cells within brain. It can cause range symptoms, including headaches, seizures, cognitive impairment, and changes in behavior. Brain tumors pose significant health concern, imposing substantial burden on patients. Timely diagnosis crucial for effective treatment patient health. be either benign or malignant, their symptoms often overlap with those other neurological conditions, leading to delays diagnosis....

Intrusion Detection Systems (IDSs) play a crucial role in safeguarding network infrastructures from cyber threats and ensuring the integrity of highly sensitive data. Conventional IDS technologies, although successful achieving high levels accuracy, frequently encounter substantial model bias. This bias is primarily caused by imbalances data lack relevance certain features. study aims to tackle these challenges proposing an advanced machine learning (ML) based that minimizes...

Acute lymphoblastic leukemia (ALL) is a lethal blood cancer that characterized by an abnormal increased number of immature lymphocytes in the or bone marrow. For effective treatment ALL, early assessment disease essential. Manual examination stained smear images current practice for initially screening ALL. This time-consuming and error-prone. In order to effectively diagnose numerous deep-learning-based computer vision systems have been developed detecting ALL peripheral (BPIs). Such...

Soil moisture plays a crucial role in various environmental processes and is essential for agricultural management, hydrological modeling, climate studies. Synthetic Aperture Radar (SAR) remote sensing presents significant potential estimating soil due to its ability operate all weather conditions provide day-and-night imaging capabilities. Among the SAR configurations, Compact Polarimetric (CP) mode has gained increasing interest as it relaxes system constraints, improves coverage, enhances...

The growth of online health communities and socially generated health-related content has the potential to provide considerable value for patients healthcare providers alike. For example, members public can acquire medical knowledge interact with others online. However, volume information-and consequent 'noise' associated large data volumes-can create difficulties users. In this paper, we present a data-driven approach better understand these from multiple stakeholder perspectives. We...

Recently, deep learning models have become more prominent due to their tremendous performance for real-time tasks like face recognition, object detection, natural language processing (NLP), instance segmentation, image classification, gesture and video classification. Image captioning is one of the critical in NLP computer vision (CV). It completes conversion from text; specifically, model produces description text automatically based on input images. In this aspect, article develops a...

Online health-related discussion provides a rich source of information for both informing the public and providing feedback to health professionals detect trends inform policy. However, there are few studies that focus on analysing sentiment in medical forum discourse. communities devoted specific conditions problems support people with similar conditions, enabling them exchange personal experiences. Analysing expressed by members community discourse can be valuable identifying particular...

Online health communities have become an important resource that both patients and family members rely on to gain medical information interact with contributors experts outside the clinical setting. However, few studies focused analysing sentiment in forum discourse. Analysing expressed by of a community discourse can be significant value, such as identifying characteristics space, determining themes predominate among large dataset, allowing people summarize topics within big data set. In...