Poster | 6th Internet World Congress for Biomedical Sciences |
Antonio J. Serrano López(1), Gustavo Camps i Valls(2), EMILIO SORIA OLIVAS(3), NICOLÁS VICTOR JIMÉNEZ TORRÉS(4), José David Martín Guerrero(5), Jose Ramon Sepulveda Sanchis(6)
(1)(6)Dpto. Electrónica. Universidad de Valencia - Burjasot. Spain
(2)Universitat de València - Burjassot, Valencia. Spain
(3)DPTO INGENIERÍA ELECTRONICA. FACULTAD DE FISICAS - BURJASSOT/VALENCIA. Spain
(4)DPTO FARMACIA Y TECNOLOGÍA FARMACEÚTICA. FACULTAD DE FARMACIA - BURJASSOT/VALENCIA. Spain
(5)G.P.D.S. Departament d´Enginyeria Electrònica. Universitat de València - Burjassot. Spain
[Pharmacology] |
[Health Informatics] |
[Oncology] |
Cancer was already known in antiquity. It is actually a group of related diseases characterized by uncontrolled multiplication and disorganized growth of the affected cells; it may arise in any of the body´s tissues.(1)
Successful treatment of cancer requires the complete removal or destruction of all cancerous tissue. Chemotherapy, treatment with drugs and hormones, has proved helpful in some forms of cancer.
Because cancer cells are similar to normal human cells, the anticancer agents are generally toxic to them and can cause numerous side effects, some of which are life threatening.
Emesis (vomits) after chemotherapy administration is one of the drawbacks in the treatment against the cancer. A control of this effect would increase the effectiveness of the healing process, therefore an estimation of patient´s reaction to treatment and antiemetic drugs is mandatory. Complexity rests in the difficulty to establish the complicated relationships between drugs and organism.
The present work exposes the development and validation of a model based on artificial neural networks (Multilayer Perceptron) which is able to predict the post-chemotherapy emesis protection level .
[Pharmacology] |
[Health Informatics] |
[Oncology] |