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579 articles for “Learning Techniques”
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A Review on Loan Approval Prediction Based on Machine Learning Techniques
Abstract: The banking industry has also benefited greatly from technological advancements. An increasing number of individuals are submitting loan applications on a daily basis. When deciding which loan applicants to approve, the bank must take certain rules into account. The bank needs to choose the best one for approval based on certain characteristics. The process of carefully verifying every person and recommending them for loan approval is laborious and fraught with …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 1–11 Read article
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Detection and Classification of Alzheimer’s Disease Using Deep Learning Technique
Abstract: It is crucial that people with Alzheimer's disease (AD) receive a proper diagnosis to begin preventative action before irreparable brain damage develops. Most people who suffer from Alzheimer's disease (AD), a neurological condition that progresses, are older than 65. The area of interest (ROI) in the hippocampus has been extensively studied for several purposes, including neurological illness research, stress development monitoring, and memory function analysis. Moreover, a connection between Alzheimer's …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 15–20 Read article
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Review on Machine Learning Techniques for Heart Failure Analysis in Health Industries
Abstract: There are few bodily components as crucial as the heart. It aids in the filtration and distribution of blood to every area of a body. The world's biggest cause of death is heart disease. It has been reported that symptoms include breathing difficulties, fast heartbeat, and chest discomfort. They analyze this data on a regular basis. This review begins with a brief introduction of cardiac disease and the present methods …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 1, 2024 · pp. 29–43 Read article
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An Expected Cardiovascular Disease Detection Using Deep Learning Techniques
Abstract: Many avoidable deaths globally are caused by CVD, often due to individuals remaining unaware of their risk factors until severe symptoms, such as heart attacks or strokes, appear. This study utilizes retinal images as the dataset to explore the potential of retinal imaging as a non-invasive diagnostic tool for early detection of cardiovascular diseases (CVD). The delay in diagnosis and treatment highlights the need for sophisticated diagnostic instruments that can …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 Read article
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Machine Learning Techniques for Predicting Industries Based on Region
Abstract: In recent years, there has been a growing interest and emphasis on agricultural land preparation and its implementation among researchers, primarily due to various factors. These factors include an increased focus within the research community, a rising demand for agricultural land, and the significance of assessing soil health for ensuring robust crop production. Picture request is one such philosophy for soil and land prosperity examination. It is a staggering measure …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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Leafguard: Smart Plant Health Detection
Abstract: Machine learning techniques, including traditional (shallow) ML, deep learning (DL), and augmented learning (AL), are being increasingly utilized for leaf disease classification. These methods involve feature extraction, data augmentation, and transfer learning to enhance model effectiveness and reduce the need for labeled data. The success of machine learning approaches in this domain hinges on the quality and quantity of data available. LeafGuard is a cutting-edge device with intelligent sensing systems …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 32–39 Read article
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Transcript Summarizer of YouTube Videos Using Deep Learning
Abstract: Transcriber Sum is a deep learning-based YouTube transcript summarization tool. It employs advanced machine learning techniques to automatically generate concise summaries of YouTube video transcripts, enabling users to quickly grasp the key content and insights of videos without the need to watch or read the entire transcript. This Transcriber Sum addresses the challenge of providing users with concise and informative summaries of video content by harnessing the power of deep …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 119–126 Read article
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Enhancing Computer Science Education through Visualization and Engagement
Abstract: The topic of visualization and engagement in computer science. This research paper attracts attention to computer science education. Computer science education is considered a very difficult course by many computer science students. But given that computer education is such an important science, this paper explores the significance of visualization techniques and engagement strategies in computer science education. Computer science education helps us understand dynamic processes such as the working of …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
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Revolutionizing Plant Disease Detection: A Comprehensive Review
Abstract: Rise in population demands more food production but the diseases in plants contribute to loss. The advancement in agricultural field has a remarkable effect in detecting plant diseases. These diseases will have a major impact on the quality of plant and yield and hence can destroy the entire plant if they are not controlled on time. To reduce disease-related losses, it is necessary to identify different types of diseases and …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 44–55 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Intelligent Optimization of Drilling Parameters in Polymer Composites using Machine Learning and Metaheuristic Techniques
Abstract: The study tests different ways to use ML and metaheuristic algorithms to determine the best drilling parameters for polymer matrix composites. The research uses a composite matrix made from 55.25% vinyl ester, 44.0% Nickel–Phosphorous coated glass fiber and 0.75% Al₂O₃ nanowires which are tested for tensile strength (64.57 MPa), flexural strength (85.86 MPa) and impact strength (71.79 kJ/m²). By applying a Taguchi orthogonal array, it is observed that a slower …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1795–1810 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Advancements in Pneumonia X-Ray Image Detection: A Review
Abstract: Pneumonia remains a primary cause of morbidness and mortality worldwide, necessitating the continuous advancement of diagnostic techniques for timely and accurate detection. Pneumonia is common, it is potentially a life-threatening infection for respiration, poses significant challenges to healthcare systems worldwide. Recently, the arrival of deep learning techniques has stirred up the field of medical imaging, offering promising avenues for enhanced pneumonia detection. In this paper, the advancements in pneumonia detection …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 1, 2025 · pp. 1–11 Read article
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Fraud Detection in Government Procurement Using Machine Learning
Abstract: Fraud represents a significant challenge in the realm of procurement, with estimates indicating that between 12 and 30% of global procurement budgets are lost to fraudulent activities (OECD, 2023). The pervasive nature of procurement fraud, which may encompass a range of deceptive practices such as bid rigging, invoice fraud, and procurement kickbacks, not only undermines the integrity of financial operations but also results in substantial losses for organizations. These losses …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 19–34 Read article
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Optimization of Lightweight Polymer Composites Using Finite Element Analysis Machine Learning and Topology Optimization Techniques for Aerospace Applications
Abstract: The advancement of aerospace engineering depends on lightweight polymer matrix composites (PMCs) because they help decrease weight while improving fuel efficiency and payload capacity together with increased structural integrity. Research developed a computer program comprising FEA with ANN and TO optimize high-performance PMCs through integrated design approaches. The combination of Python-controlled LS-DYNA simulations measured hybrid composite laminate resistance to impact while an ANN model obtained data from simulations to forecast …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 693–709 Read article