<![CDATA[Nutrition plays a crucial role in clinical practice, impacting immune function, disease prevention, and treatment. However, assessing a patient’s nutritional status remains challenging due to individual differences and the limitations of traditional methods like dietary recalls and food diaries, which can be subjective and time-consuming. Artificial Intelligence (AI), particularly machine learning, is emerging as a powerful tool to enhance nutritional assessments. AI can quickly and accurately analyze large datasets, enabling both patients and clinicians to track and manage dietary intake, blood sugar levels, and other health metrics through apps and wearable devices. Despite its promise, AI in nutrition faces challenges such as data accuracy, potential misdiagnoses, and ethical concerns related to data privacy and security. Nonetheless, as technology advances, AI is set to play an increasingly significant role in nutrition diagnostics and healthcare, offering new possibilities for personalized and efficient nutritional management.]]>
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