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Siranjeevi Gurumani

Decision Scientist • 12m

Neural networks are poised to play a major role in improving predictability and treatment outcomes. However, achieving personalized treatment through precision medicine still requires significant progress. Identifying core mechanisms of action is essential to bridge the gap between theoretical predictions and clinical application, making AI-driven recommendations more acceptable to doctors. Advancements in AI have significantly boosted personalized treatment by enabling the analysis of vast and complex datasets. This allows for more accurate diagnostics, better prediction of disease progression, and tailored treatment plans that consider individual patient characteristics. While there is still much work to be done, the integration of AI in healthcare promises to enhance treatment efficacy and improve patient outcomes, paving the way for truly personalized medicine.

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