AI in Healthcare: Revolutionizing Patient Diagnosis and Treatment
Abstract
Artificial Intelligence (AI) is transforming healthcare by enhancing diagnostic accuracy and personalizing treatment plans. This study investigates the application of AI in diagnosing diseases and optimizing treatment strategies. Through the analysis of patient data using machine learning algorithms, we demonstrate significant improvements in early disease detection and treatment outcomes. The integration of AI in healthcare settings has the potential to reduce misdiagnoses, streamline workflows, and improve patient care. Our findings highlight the transformative impact of AI on healthcare and its potential to revolutionize medical practices.
Keywords
References
- LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444.
- Breiman, L. (2001). Random Forests. Machine Learning, 45(1), 5-32.
- Smola, A. J., & Schölkopf, B. (2004). A tutorial on Support Vector Regression. Statistics and Computing, 14(3), 199-222.
- Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115-118.
- Obermeyer, Z., & Emanuel, E. J. (2016). Predicting the future—big data, machine learning, and clinical medicine. The New England Journal of Medicine, 375(13), 1216-1219.
How to Cite
License
Copyright (c) 2024 Journal of Technology

This work is licensed under a Creative Commons Attribution 4.0 International License.
Similar Articles
- Hugo Tom, David Kim, Emily Parker, Advanced Threat Detection Using Machine Learning Algorithms , Journal of Technology: Vol. 2 No. 1 (2024): The Future of Renewable Energy Technologies
- Robert Lee, Anna Smith, Explainable AI: Enhancing Transparency and Trust in Artificial Intelligence Systems , Journal of Technology: Vol. 2 No. 2 (2024): Advances in Artificial Intelligence
- David Brown, Lisa Green, AI-Driven Cybersecurity: Enhancing Threat Detection and Response , Journal of Technology: Vol. 2 No. 2 (2024): Advances in Artificial Intelligence
- Jessica Taylor, Mark Anderson, AI-Powered Predictive Maintenance in Manufacturing: Enhancing Efficiency and Reducing Downtime , Journal of Technology: Vol. 2 No. 2 (2024): Advances in Artificial Intelligence
- Hugo Tom, Emily Thompson, Michael Lee, Enhancing Autonomous Robotic Navigation Through Reinforcement Learning , Journal of Technology: Vol. 2 No. 2 (2024): Advances in Artificial Intelligence
- Hugo Tom, Sarah Brown, James Miller, Integrating Robotics and the Internet of Things (IoT) for Smart Automation , Journal of Technology: Vol. 2 No. 2 (2024): Advances in Artificial Intelligence
- Susan Miller, James Walker, Angela Green, Advancements in 5G Technology: Implications for Smart Healthcare Systems , Journal of Technology: Vol. 1 No. 1 (2024): Special Issue: Emerging Technologies in Artificial Intelligence
- Sarah Wilson, John Davis, AI-Driven Autonomous Vehicles: Enhancing Safety and Efficiency , Journal of Technology: Vol. 2 No. 2 (2024): Advances in Artificial Intelligence
- Linda Robinson, Michael Brown, Hannah Lee, Augmented Reality (AR) in Education: Transforming Learning Experiences , Journal of Technology: Vol. 1 No. 1 (2024): Special Issue: Emerging Technologies in Artificial Intelligence
- Alice Johnson, Robert Lee, Maria Garcia, Enhancing Autonomous Vehicle Navigation Using Deep Reinforcement Learning , Journal of Technology: Vol. 1 No. 1 (2024): Special Issue: Emerging Technologies in Artificial Intelligence
You may also start an advanced similarity search for this article.