Publications by authors named "Alfredo Minguela Puras"
Article Synopsis
- Children with a type of cancer called acute lymphoblastic leukaemia (ALL) usually have good chances of survival, but some of them might get sick again (called relapse).
- Researchers are using a special method called topological data analysis (TDA) to look at patient data and predict who is more likely to relapse, especially those who were thought to be low risk.
- They suggest three ways to analyze data to help doctors understand the risks better, using things like visual checks or advanced math and machine learning with certain important markers (CD10, CD20, CD38, and CD45).
Background: Alcoholic cirrhosis (AC) is a common cause of death among individuals abusing alcohol. In the last resort, liver transplantation (LT) is considered the only solution to save the patient's life, generating socioeconomic and public health problems. Clinical and sociodemographic characteristics, rejection frequency, and short- and long-term graft survival are not well known in end-term AC patients undergoing LT.
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