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211 articles for “medical machine learning”
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An innovative antibiotic "Abaucin": Instigated by Artificial Intelligence
Abstract: Nosocomial Gram-negative pathogen, Acinetobacter baumannii repeatedly demonstrates multidrug resistance. Discovering novel antibiotics against A. baumannii has proven thought-provoking through conventional screening tactics. Providentially, machine learning approaches allow for the speedy exploration of chemical space, snowballing the probability of determining new antibacterial molecules. In the following research era, a neural network is accomplished with growth reserve dataset and accomplished in silico predictions for structurally unconventional molecules with commotion in divergence to …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 13, Issue 3, 2023 · pp. 29–33 Read article
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Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
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Application of Machine Learning Techniques for Tongue Diagnosis in Ayurveda
Abstract: The analysis of tongue image is a very crucial approach in order to evaluate human health in Ayurveda medication. As a result of the modification in tongue color might counsel physical or mental disorders. Many tongue color quantification strategies for tongue diagnosis are published by many researchers in Chinese medication. However, reliable tongue color analysis algorithms are limited for Ayurveda medicine. The main objective of this paper is to apply …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 1, 2020 · pp. 8–14 Read article
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A Review of Various Deep Learning Models for Classification of BrainTumor
Abstract: Brain Tumor is most challenging and life threading decease now these days. Timely accurately detection of brain tumor is play important role for patient health improvement and it increase life survival rate. Traditional of brain tumor detection relay heavily on manual interpretation of medicalimage, it is very time consuming and chance to human error in detection of brain tumor. Now in recent advancement of Artificial intelligence (AI), Machine learning (ML) …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Machine Learning Techniques for Early Detection of Heart Disease
Abstract: Cases of heart disease are increasing rapidly, thus it's important and concerning to be aware of any potential ailment beforehand. This diagnosis is a difficult task that must be completed fast and precisely. The primary goal of this study is to determine which patient, based on different medical features, has a higher chance of having heart disease. We created a heart disease prediction algorithm based on the patient's medical history …
Published in Journal of Microelectronics and Solid State Devices · Vol. 10, Issue 3, 2023 · pp. 16–21 Read article
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Role of Machine Learning and Internet of Things in Health Care System: A Review
Abstract: AbstractNowadays, integration of Machine Learning and IoT is modern technology for solving problems in healthcare industries. As IoT is entering into healthcare, the expectation of getting new facilities is also increasing, especially for the elderly. A number of protocols are affected on healthcare applications. IoT in healthcare is gaining more attention due to the advancement in the development of IoT devices. Comparative analysis of machine learning algorithms with their application …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 3, 2020 · pp. 40–51 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Analysis of Machine Learning Algorithms for the Detection of Mental Health Problems in Employees
Abstract: Mental health-related issues are more critical issues in the workplace. Mental health has been a major and challenging issue, especially for working professionals. A bad work environment can cause a variety of physical and physiological problems as well as decreased productivity. People are reluctant to ask for help from mental health specialists, according to studies. The fundamental reason for this is the stigma attached to mental illness. Working professionals therefore …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 3, 2022 · pp. 12–24 Read article
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Optimizing Heart Disease Prediction: Comparative Analysis of Machine Learning Algorithm for Early Detection
Abstract: The expanding realm of data analysis holds considerable importance in healthcare, particularly in the medical sector where forecasting heart disease is considered a complex endeavor. Early prediction of serious health conditions can be the determining factor between survival and fatality, with heart disease being one such critical health issue. Over the past decade, the main reason for death has been heart disease. Heart disorders come in many different forms, and …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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A Survey on Image Forgery Detection Techniques Using Machine Learning Approaches
Abstract: With the advent of newer technologies and usage of data in various service fields like education, commercial and healthcare, etc. The possibility of tampering and altering the data in the form of media like images is easily seen to derive various illegitimate benefits and outcomes. The rapid advancements in technology and the increased utilization of data in various service sectors such as education, commerce, healthcare, etc., have raised concerns about …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 2, 2023 · pp. 17–26 Read article
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An Analytical Review of Machine Learning Methodologies
Abstract: Machine Learning (ML) is a dynamic and rapidly developing area of computer science that enables the system to learn from data and improve its performance without clear programs. Rooted in statistical theory and computer algorithms, ML has become a major technology that progresses in artificial intelligence. It strengthens the detection of the recommendations and speech for extensive applications from autonomous vehicles and medical diagnoses. This paper has reviewed the basics …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 13–21 Read article
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Breast Cancer Detection Using Deep Learning
Abstract: Breast cancer, according to the Breast Cancer Institute, is one of the most difficult kinds of cancer that is extremely threatfulfor women all over the world. Early cancer discovery, followed by appropriate treatment, can help minimize the risk of deaths in the first stage of respective cancer only and increase the likelihood of survival by up to 8%. Medical imaging research has become increasingly reliant on machine learning and deep …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 1, 2022 · pp. 33–42 Read article
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Early Detection of Heart Disease using Machine Learning Techniques
Abstract: Coronary illness stays one of the main sources of death around the world. Exact expectations of coronary illness can altogether work on quiet results by empowering early intercession and customized treatment plans. Throughout the course of many recent years, AI (ML) methods have been extensively investigated for anticipating coronary illness, attribuFig to their remarkable capacity to analyze complex data patterns and generate precise predictions based on historical clinical records. With …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 34–45 Read article
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Comprehensive Review of Adenoid Cystic Carcinoma: Pathogenesis, Diagnosis, and Emerging Therapeutic Approaches
Abstract: Adenoid cystic carcinoma (ACC)is an infrequent neoplasm, highly malignant, that develops mainly in the salivary glands with the potential to exist in any secretory glandular sites, including the lacrimal glands, breast, and respiratory tract. ACC usually has a benign initial course, but conversely, it is notoriously aggressive in behavior with high incidence of perineural invasion, local recurrence, and distant metastasis, mostly to the lungs. The tumor’s molecular features are characterized …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–17 Read article
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Technology-Based Interventions for Diabetes Self-Management: A Review of Mobile Apps, wearable Devices, and Telemedicine Solution
Abstract: This comprehensive review delves into the transformative impact of technological innovations on diabetes management. From historical insights to cutting-edge developments, we explore the evolution of diabetes care through wireless sensors, smart devices, AI-driven solutions, and telemedicine. Investigating sensor-augmented pump systems, biosensor-based glucose monitoring, smart pens, and telemedicine solutions, we uncover their efficacy in enhancing patient self-management and healthcare accessibility. Furthermore, the convergence of machine learning, data mining, and artificial intelligence …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 13, Issue 2, 2023 · pp. 25–35 Read article
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Pharma Guard: Smart Medication Management System
Abstract: Pharma Guard Smart Medication Management System presenting a comprehensive overview of an innovative technology designed to revolutionize medication management in healthcare settings. In an era of advancing digital solutions, the Pharma Guard system offers a sophisticated approach to ensuring medication safety and adherence. Through the integration of smart technology, including internet of things (IoT) devices and machine learning algorithms, Pharma Guard enables real-time monitoring, tracking, and management of medication consumption …
Published in International Journal of Mobile Computing Technology · Vol. 2, Issue 1, 2024 · pp. 30–37 Read article
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Disease Prediction for Heart using Data Mining Techniques and Decision Tree Classification
Abstract: Heart disease is a prominent cause of death worldwide, and many people are concerned about it. Early detection of heart disease becomes very crucial and has the potential to save many lives. However, detecting cardiovascular diseases such as heart attacks, coronary artery disease, and others of similar types is a critical challenge presented by routine clinical data analysis, even by using well known algorithms. We can’t risk lives of people …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 2, 2022 · pp. 16–22 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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Disease Prediction Android Application using Machine Learning
Abstract: The rapid proliferation of internet technology and handled devices has opened up new avenues for an online healthcare system. There are instances where online medical help or healthcare advice is easier and faster to grasp than real world help. People often feel reluctant to go to hospital or visit doctors for minor symptoms. However, in many cases, these minor symptoms may trigger into a major health hazard. As online wellbeing …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 8, Issue 1, 2021 · pp. 1–9 Read article