AI-DRIVEN SOLUTIONS FOR HEALTHCARE: IMPROVING DIAGNOSTICS AND TREATMENT THROUGH MACHINE LEARNING
Keywords:
AI, Diagnosis, Health, Healthcare Industry, Machine Learning (ML)Abstract
The use of AI and machine learning has great potential to revolutionise medical diagnosis and treatment. This study analyses the potential of various instruments in healthcare by comparing their advantages, disadvantages, and uses. Machine learning systems have the ability to detect patterns, improve the accuracy of diagnoses, and bolster expert opinion. However, poor data quality, an absence of interpretability, and problems with execution may limit their effectiveness. Conversely, AI has the potential to augment clinical judgement, improve patient outcomes, and increase healthcare efficiency. However, concerns about data safety, limited generalisability, and regulatory compliance can make its implementation challenging. It is crucial to comprehend these advantages and limitations to guarantee the efficient implementation and endorsement of these technologies in healthcare. As a whole, healthcare services will be improved because future healthcare providers can use AL and ML to make better decisions about patient evaluation and treatment alternatives.
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