Search
211 articles for “medical machine learning”
-
Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
-
Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
-
Innovations in Gene Therapy: Revolutionizing Treatment for Genetic Disorders and Diseases
Abstract: Gene therapy is a revolutionary intervention in the treatment of genetic diseases since it is an intervention that aims at the very source of diseases, through editing and modification of genes. More recent innovations in gene editing systems, such as CRISPR-Cas9, CRISPR-Cas12, and prime editing, have greatly increased the accuracy and effectiveness of gene therapies, enabling more specific therapies. The opportunities of personalized medicine are also extended by the creation …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 16, Issue 1, 2026 · pp. 19–25 Read article
-
Physical Modeling of Mass Transport Processes in Extraterrestrial Landscapes
Abstract: Currently the progress in physical models based on mass transport in both the Earth's surface and extraterresterial landscape has been growing. It is a frame work involving different natural and made made processes including aeline process, fluid flow process, magmal movement, Geomagnetic stroms, and clould flow modesl etc. These process encorporates Physical models and appraches which help to simulate, compute and experiment in order to reduce complexity. However, their operating …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 47–54 Read article
-
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 · pp. 10–20 Read article
-
AI Based Dental Care Solution System
Abstract: The AI-Based Dental Care Solution System is a web-based healthcare application developed using the MERN stack (MongoDB, Express. js, React.js, and Node.js) and integrated with Artificial Intelligence techniques to support early and accessible dental self-assessment. The system assists users in preliminary dental consultation by collecting symptoms such as tooth pain, sensitivity, swelling, bleeding gums, and bad breath through both structured forms and a conversational chatbot interface. Using Natural Language Processing …
Published in Research and Reviews: A Journal of Dentistry · Vol. 17, Issue 2, 2026 Read article
-
An Innovative AI-Integrated Approach for Identifying the Tensile Robustness of Polymeric Materials
Abstract: Polymeric materials have so many applications and character similar to flexibility, robustness and lightweight nature they are essential to a large variety of industries. Though, it is difficult to establish their tensile robustness appropriately, particularly in a variety of environmental situation. Provide a recommended Artificial Intelligence (AI)-integrated method to decide the issues of rapidly ascertaining the tensile robustness of the polymeric material. Using machine learning (ML), this study, predicted and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 90–97 Read article
-
A Comprehensive Review of AI-Driven Strategies for Tailored Wellness and Dietary Recommendations
Abstract: In today’s fast-paced world, health and fitness have become top priorities for many individuals. As a result, people increasingly turn to mobile apps and digital tools to track their wellness goals, follow diet plans, and stay fit. However, most of these apps provide the same set of recommendations for all users, ignoring the fact that everyone has different needs. This one-size-fits-all approach often fails to keep users engaged and motivated, …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 16–20 Read article
-
Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 Read article
-
Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
-
Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
-
Nano-Enhanced Biosensors: Bridging the Gap in Early Disease Detection and Diagnosis
Abstract: This article provides an in-depth examination of nano-enhanced biosensors, a groundbreaking technology that combines nanotechnology and biosensing techniques to transform disease detection and diagnosis. These advanced sensors boast exceptional sensitivity, specificity, and rapid response times, enabling early detection and treatment of various medical conditions. The article covers the fundamental principles, current applications, and prospects of nano-enhanced biosensors in multiple medical domains, including recent research, experimental investigations, and case studies. It …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 2, 2024 · pp. 10–17 Read article
-
Prediction of Prostate Cancer Using Boosting Technique
Abstract: There are many diseases that are associated with humans, but some diseases might be associated with only males or only females. This paper shows and discusses the disorder that is associated mainly in men. Prostate cancer is associated with the example of illness. Usually when the damaged cells develop in the prostate gland occurs prostate cancer occurs. These cells increase uncontrollably. Reports given by the researchers show that this is …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 1–9 Read article
-
Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
-
A Real-life Healthcare Chatbot with IBM Cloud Services in Python
Abstract: A chatbot or conversational specialist is a product that can speak with a human by utilizing normal language. One of the fundamental undertakings in computerized reasoning and normal language handling is the demonstrating of discussion. Since the start of man-made brainpower, it has been the hardest task to make a decent chatbot. Despite the fact that chatbots can perform numerous errands, the essential capacity they need to play is to …
Published in Recent Trends in Programming languages · Vol. 8, Issue 2, 2021 · pp. 1–4 Read article
-
A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes
Abstract: One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection. However, low contrast, noise, organ similarity, and tumor shape and size variability make it difficult to accurately identify and segment liver tumors from medical imaging. Automated liver cancer diagnosis, segmentation, and prognosis have been greatly improved by recent developments in artificial intelligence (AI), especially deep learning. This work presents …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 39–47 Read article
-
Medical Image Processing Using Data Science: A Review
Abstract: The purpose of this work is to introduce data science in medical imaging. Both theoretical advancements and real-world applications are covered in this research work. The healthcare industry is distinct from all other industries and is a special sector. It is a top-priority industry that consumes a sizable percentage of the federal budget. In general, only doctors can analyses images, but thanks to technology, we are now able to use …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 3, 2022 · pp. 7–15 Read article
-
Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
-
Magnetic and Radioactive Nanoparticles for Improved Theranostics and AI Assisted Radiation Therapy
Abstract: Nanoparticles based therapeutic and theranostics technique is becoming an active area of research in nanomedicine. The sensitivity, biocompatibility, and stability of magnetic and radioactive nanoparticles determine their functionality. This research highlights the impacts of magnetic and radioactive nanoparticles on therapeutic techniques namely, cell therapy, gene therapy, and tissue regeneration. Then, it is intended to brief a principal role of these therapeutic techniques to envisage theranostics medicine and radiation therapy using …
Published in International Journal of Advance in Molecular Engineering · Vol. 3, Issue 2, 2025 · pp. 10–21 Read article
-
Study and Research Survey of Machine Learning on Different Field for Next Research Directions
Abstract: Machine learning (ML) is a part of artificial intelligence (AI). ML is a brain of AI, which works to same to same as human creature. ML used to several learning algorithms is a part of related learning techniques as supervised, unsupervised, reinforcement, deep and deep-reinforcement learning techniques. ML used on various research fields as, cyber security, big data, IOT, big code naturalness, flood prediction, ultra sound computer-aided diagnostic system, medicine …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 2, 2020 · pp. 46–55 Read article