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196 articles for “artificial intelligence in healthcare”
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Advancements in Reinforcement Learning: A Comprehensive Analysis of Algorithms, Applications, and Future Directions in Artificial Intelligence
Abstract: This work provides an overview of Reinforcement Learning (RL), an important field of artificial intelligence (AI) aims to provide the long-term benefits by learning a relating with a given environment. It spells out everything, what agents and environments do, to how rewards, states, and behaviours. It spent lot of time on looking the most usable RL algorithms, like DQN, SARSA, and Q-Learning. These studies provide a clear view of RL. …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 17–22 Read article
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TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article
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Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems. Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Leveraging AI and Machine Learning for Early Prediction and Prevention of Non- Communicable Diseases in Resource-Limited Settings
Abstract: Populations in these regions face persistent structural barriers, such as underdeveloped healthcare infrastructure, shortages of trained health professionals, and fragmented or incomplete health information systems. These limitations delay timely diagnosis, restrict access to preventive care, and compromise effective disease management. In recent years, rapid progress in artificial intelligence (AI) and machine learning (ML) has opened promising avenues to mitigate these challenges. Practical applications already emerging include mobile health platforms for …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 9–15 Read article
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Artificial Intelligence and the Future of Education
Abstract: Artificial Intelligence (AI) refers to the capability of a computer system to mimic human intelligence by performing tasks such as learning, reasoning, problem-solving, and decision-making. As a rapidly evolving and emerging technology, AI holds the potential to transform a wide range of sectors, including healthcare, transportation, business, and notably, education. Its application in the educational domain is gaining momentum, aiming to create more efficient, engaging, and personalized learning environments. Incorporating …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 39–44 Read article
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Graphene Based Electronic Skin for Wearable Health Monitoring and Human– review on Machine Interaction, Materials, Structures and AI Integration
Abstract: Graphene-based electronic skin (e-skin) has emerged as a transformative technology for next-generation wearable health monitoring and advanced human–machine interaction (HMI). Owing to its outstanding electrical conductivity, mechanical flexibility, atomic-scale thickness, and biocompatibility, graphene enables the fabrication of ultrathin, conformal, and multifunctional sensors capable of mimicking the sensory functions of natural human skin. Over the past decade, research in this domain has progressed rapidly across four interconnected fronts: material synthesis and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Advances in Stimuli-Responsive Smart Drug Delivery Systems: A Systematic Review
Abstract: Imagine a world where medicines work smarter, not harder. Stimuli-responsive drug delivery systems (SRDDS) are transforming healthcare by releasing therapeutic agents in response to specific triggers. These triggers can be internal, like changes in pH or temperature, or external, like light or magnetic fields. By leveraging these triggers, SRDDS can optimize treatment and minimize side effects. The potential applications of SRDDS are vast, from cancer treatment to gene delivery and …
Published in Trends in Drug Delivery · Vol. 13, Issue 2, 2026 Read article
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Pharmacogenomics: Unlocking the Genetic Basis of Drug Response for Precision Medicine
Abstract: Pharmacogenomics, a fusion of pharmacology and genomics, explores how genetic variations influence individual responses to medications. This field is revolutionizing modern medicine by moving away from a one-size-fits-all approach toward personalized treatment strategies. By identifying specific genetic markers, pharmacogenomics aims to enhance drug efficacy, minimize adverse drug reactions, and improve overall patient outcomes. Key methodologies in this discipline include candidate gene analysis, genome-wide association studies, and haplotype analysis, all of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 52–59 Read article
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Role of Artificial Intelligence in Structural Health Monitoring-A Brief Evaluation
Abstract: Artificial intelligence (AI) refers to the capacity of a machine or a computer to ‘think’ or reason in the way a human would, utilizing experience, learned facts, and flexible rules to solve problems that may not fit the standard outlines for a normal algorithm. From this follows the utilization of AI in various sectors, such as the information technology (IT) industry, media, healthcare and medicine, logistics, environmental sustainability, finance, business, …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 34–39 Read article
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AI-Driven Precision Nutrition: Advancing Personalized Dietary Systems for Public Health Equity in Resource-Constrained Environments
Abstract: The dual burden of malnutrition and diet-related non-communicable diseases (NCDs) represents a growing global public health challenge, particularly in low- and middle-income countries. Traditional dietary guidelines are largely population-based and fail to account for individual variability in genetics, metabolism, lifestyle, and environmental exposure. This limitation has led to the emergence of precision nutrition, an evolving field that integrates biological data and computational intelligence to deliver personalized dietary recommendations. This paper …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Academia to Industry: The Impact of AI on Information Retrieval Technologies
Abstract: Artificial intelligence (AI) has significantly reshaped the field of information retrieval (IR), bridging theoretical advancements from academia with practical applications across various industries. This article explores the transformative impact of AI on IR technologies, highlighting key contributions from academic research and how they have been adapted for industry-scale implementations. Academic innovations, such as neural ranking models and semantic search techniques, have improved the accuracy and relevance of search results by …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Personalized Nutrition and Exercise: Pioneering the Path to Precision Medicine
Abstract: Preventive healthcare is about to undergo a major shift thanks to the personalised exercise and nutrition paradigm, which is based on precision medicine concepts. In order to create tailored recommendations for improving health outcomes and preventing chronic diseases, this article explores the integration of genetic profiling, metabolic evaluation, and lifestyle factors. A person's response to food and exercise depends heavily on genetic and metabolic variances, which emphasises the need of …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 2, 2024 · pp. 42–46 Read article
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Intelligent Medical Devices and Robotics in Modern Healthcare: Technological Advancements and Economic Considerations
Abstract: The integration of robots and intelligent medical devices in intensive care units (ICUs) represents a significant advancement in healthcare technology. These systems, including robotic assistants, automated monitoring tools, and AI-powered diagnostic devices, are designed to enhance patient care, streamline workflows, and reduce human error. Robots in the ICU can assist with routine tasks such as medication delivery, patient repositioning, and even basic surgeries, enabling healthcare professionals to focus on critical …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 18–27 Read article
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The Role of Artificial Intelligence in Mental Health: Applications in Neurodegenerative Disorders
Abstract: Artificial intelligence (AI) has significantly changed many aspects of medical care, particularly the early evaluation, therapy, and management of neurodegenerative illnesses like Alzheimer's, disease, Parkinson's diseases, and Huntington's diseases. The current research explores the application of AI in mental health with respect to neurological disorders, especially advancements in cognitive examination, neuroimaging analysis, predictive modeling, and customized therapy modalities. Artificial intelligence (AI) systems have shown enormous potential in detecting minute biomarkers …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 · pp. 34–40 Read article
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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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Ensuring Data Traceability Across Multiple Cloud Environments
Abstract: This study investigates the challenges and solutions for ensuring data traceability across multiple cloud environments. With organizations' increasing reliance on cloud infrastructure, maintaining data traceability is crucial for compliance, data integrity, and secure data management. The diversity of cloud systems, spanning public, private, and hybrid models, introduces complexities in tracking data lineage, access, and movement. This study delves into multi-cloud strategies' technical and operational hurdles, such as varying data formats, …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 08–22 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 Read article
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Privacy Preservation Methods in Multimedia Applications: A Comprehensive Review
Abstract: This comprehensive review explores the current landscape of privacy preservation techniques in multimedia applications, offering a detailed examination of their effectiveness, limitations, and future directions. As the use of multimedia data continues to grow across diverse sectors such as healthcare, surveillance, social media, and entertainment, ensuring the confidentiality and integrity of this data has become a pressing concern. The study covers a broad spectrum of privacy-preserving approaches, from conventional cryptographic …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 33–41 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article