Top Tweets for #MPPHep
#PrecisionMedicine holds promise for better tailoring of care. Achieving the right balance between #PrecisionMedicine and #PersonalizedMedicine is still an umet need.
Ending the I Consenso #MPPHep with a comprehensive lecture from Professor Llovet.
@AEEHLiver #LiverTwitter
Closing lecture in #MPPHep by Prof. @JMLlovet integrating precision medicine in daily care of patients living with liver cancer @AEEHLiver #1st Consensus on Precision Medicine in liver diseases Seville.
👉🏾Actionable therapeutic targets in HCC lower than 5% @EASLedu @AASLDtweets
Segunda Jornada del I Consenso #MPPHep @AEEHLiver
Brillantes ponencias:
✅Genética para el diagnóstico, y manejo de enfermedades colestásicas, metabólicas, y parenquimatosas @JesusQuintero @ZoeMario2 @PiotrSocha
✅HAI: LMS (cT1), epigenetica y farmacogenetica @macarlotal
Guau!
Brilliant session #MPPHep in liver cancer from radiomics to digital and molecular pathology and HCC, iCCA & pediatric tumors.
Speakers: 👏Leonor, Julien, Maria, Txus & Carolina👏
Chairs: @Alexfornergon @BMnguez
We’re in the correct pathway close to the success @AEEHLiver
Propuesta disruptiva @mikelhernaez abordando la incertidumbre en la inteligencia artificial mediante el análisis de la entropía @CIMA_unav @AEEHLiver #MPPHep La mejor opción para generar hipótesis que puedan testarse. Jornadas de primavera en Sevilla siempre abriendo camino 👏🔟
#MPPHep Brilliant talk by @xdopazo about precision screening based on AI & RWE looking for an algorithm trained and validated in hundreds thousands cases to identify people at risk of chronic hepatitis C in Andalucia @AEEHLiver @GileadSciences @saludand @EASLnews @IAVANTE_FPS 🔟
Fantastic talk by @HerbertTilg about microbiome in liver diseases un tackling gut-liver axis: bacteria (loved akkermansia muciniphila)>end-products (bile acids, Short Chain Fatty Acids)>gut permeability. A fascinating field #MPPHep @AEEHLiver @EASLnews @CIBERehd
#MPPHep en #SindromedeAlagille @DrAntonioOlveira desde el diagnóstico genético secuenciando JAG-1 & NOTCH2 a la IA en imagen analizando caras y el estudio familiar (enfermedad autonómica dominante) y el tratamiento con maralixibat mejora el pronóstico @AEEHLiver @IdiPAZScience
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