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+imaging+and+Time-Activity+Curve+(TAC)+analyses+are+essential+for+understanding+and+quantifying+the+biodistribution+of+radiopharmaceuticals+over+time+and+space.+Traditional+compartmental+modeling%252C+while+foundational%252C+commonly+struggles+to+fully+capture+the+complexities+of+biological+systems%252C+including+non-linear+dynamics+and+variability.+This+study+introduces+an+innovative+data-driven+neural+network-based+framework%252C+inspired+by+Reaction+Diffusion+systems%252C+designed+to+address+these+limitations.+Our+approach%252C+which+adaptively+fits+TACs+from+dPET%252C+enables+the+direct+calibration+of+diffusion+coefficients+and+reaction+terms+from+observed+data%252C+offering+significant+improvements+in+predictive+accuracy+and+robustness+over+traditional+methods%252C+especially+in+complex+biological+scenarios.+By+more+accurately+modeling+the+spatio-temporal+dynamics+of+radiopharmaceuticals%252C+our+method+advances+modeling+of+pharmacokinetic+and+pharmacodynamic+processes%252C+enabling+new+possibilities+in+quantitative+nuclear+medicine.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.74e5b317fd7f962abd8b99cdde16824d%3frik%3dBGNxb7ObZBdBwA%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Data-Driven+Parametric+Design&simid=608017166660810378&FORM=IRPRST&ck=4FC6E1CD830AE69F31732614CAE132D6&selectedIndex=33&itb=0)
