Published 16-04-2024
Keywords
- AI,
- medical imaging,
- disease detection,
- disease classification
How to Cite
Abstract
Medical imaging plays a crucial role in the early detection and classification of various diseases. Recent advancements in artificial intelligence (AI) have shown promising results in analyzing medical images for disease detection and classification. This paper explores the use of AI-driven approaches in medical imaging analysis, focusing on the detection and classification of diseases such as cancer, cardiovascular diseases, and neurological disorders. We discuss the challenges and opportunities associated with AI-driven medical imaging analysis and review recent research and developments in the field. Additionally, we examine the impact of AI on improving diagnostic accuracy, treatment planning, and patient outcomes.
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References
- i Pillai, Aravind Sasidharan. "A Natural Language Processing Approach to Grouping Students by Shared Interests." Journal of Empirical Social Science Studies 6.1 (2022): 1-16.
- ii Venigandla, Kamala, and Venkata Manoj Tatikonda. "Improving Diagnostic Imaging Analysis with RPA and Deep Learning Technologies." Power System Technology 45.4 (2021).
- iii Pulimamidi, R., and P. Ravichandran. "Enhancing Healthcare Delivery: AI Applications In Remote Patient Monitoring." Tuijin Jishu/Journal of Propulsion Technology 44.3: 3948-3954.
- iv Kumar, Mungara Kiran, et al. "Approach Advancing Stock Market Forecasting with Joint RMSE Loss LSTM-CNN Model." Fluctuation and Noise Letters (2023).
- v Pargaonkar, Shravan. "Quality and Metrics in Software Quality Engineering." Journal of Science & Technology 2.1 (2021): 62-69.
- vi Venigandla, Kamala, and Venkata Manoj Tatikonda. "Optimizing Clinical Trial Data Management through RPA: A Strategy for Accelerating Medical Research."