Driving Medical Diagnostics Forward: The Role of AI in Innovation and Implementation
Keywords:
Artificial Intelligence, Diagnostics, Radiology, Dermatology, Machine Learning, Deep Learning, Disease DetectionAbstract
The revolutionary effects of artificial intelligence (AI) on diagnostic procedures in radiology pathology and dermatology are examined in this article. The aim is to conduct thorough analysis of incorporation of AI technologies in these domains. It highlights capacity to augment diagnostic precision and efficacy. This study emphasizes developments in AI algorithms such as deep learning and machine learning. Their applications include disease diagnosis. Image analysis and prognostic assessments are also considered. Methodically evaluating literature from top databases important discoveries show that AI has greatly increased workflow
automation. Diagnosis accuracy has improved significantly. However, issues with data quality model interpret ability and interface with current clinical systems still exist. The paper also touches on moral and legal issues relevant to use of AI in diagnosis. This study advocates for further research. This research aims to overcome current limits. It should better optimize AI-driven diagnostic tools. The paper ends with insights into emerging patterns and future prospects.
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References
Mirbabaie, M., Stieglitz, S., Frick, N.R.: Artificial intelligence in disease diagnos- tics: A critical review and classification on the current state of research guiding future direction. Health and Technology 11(4), 693–731 (2021)
Fujita, H.: Ai-based computer-aided diagnosis (ai-cad): the latest review to read first. Radiological physics and technology 13(1), 6–19 (2020)
Ahmad, Z., Rahim, S., Zubair, M., Abdul-Ghafar, J.: Artificial intelligence (ai) in medicine, current applications and future role with special emphasis on its potential and promise in pathology: present and future impact, obstacles including costs and acceptance among pathologists, practical and philosophical considerations. a comprehensive review. Diagnostic pathology 16, 1–16 (2021)
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