The present article is published in Proche-Orient Chrétien, N.66, VOL.3-4, JAN. 2017, USJ: Beirut, pp. 425-430. It is a philosophical review of Philippe Capelle-Dumont and Yannick Courtel book “Religion et Liberté” that fetches the records of the First International Symposium of the Francophone Society of Philosophy of Religion about the two concepts Religion and Freedom. On one hand, religion has always been considered as a pole of practices and references contrary to freedom declining a dependence on a "binding doctrine"; on (...) the other hand, religion has undergone several political representations in the many spaces of cultural, social and international life which is urgent to re-examine. The article proposes a synthesis of the conferences of Philippe Capelle-Dumont, Jean-Luc Marion, Jean Greisch, Joseph O’Leary, François Chenet, Souleymane Bachir Diagne, Francis Jacques, Pierluigi Valenza, Danielle Cohen-Levinas, Yannick Courtel and Jean Grondin who concludes with the “freedom to philosophize about religion”. (shrink)

RESUMENDesde la teoría postcolonial se han cuestionado los modelos de historia de las ideas impuestos por el africanismo y el orientalismo. Diferentes teóricos africanos –Bachir Diagne, Mundimbe, Wiredu o Kete Asante– han formulado diversas soluciones para superar las dificultades. Este trabajo explora las principales dificultades y las propuestas para elaborar una historia de la Filosofía africana. -/- The postcolonial theory was questioning the patterns of History of Ideas imposed by Orientalism and Africanism. Different African theorists –Bachir (...) class='Hi'>Diagne, Mundimbe, Kete Asante or Wiredu– developed various solutions to overcome the dificulties. This paper explores the principal challenges and proposals so as to build a History of African philosophy. (shrink)

Breast cancer remains a significant health concern worldwide, necessitating the development of effective diagnostic tools. In this study, we employ a neural network-based approach to analyze the Wisconsin Breast Cancer dataset, sourced from Kaggle, comprising 570 samples and 30 features. Our proposed model features six layers (1 input, 1 hidden, 1 output), and through rigorous training and validation, we achieve a remarkable accuracy rate of 99.57% and an average error of 0.000170 as shown in the image below. Furthermore, our investigation (...) identifies the most influential features in breast cancer diagnosis, shedding light on the key determinants of malignancy. Notably, we find that factors such as fractal dimension_se, symmetry worst, compactness_worst, symmetry_se, and smoothness_se play pivotal roles in distinguishing between benign and malignant cases. This research contributes to the ongoing efforts to enhance breast cancer diagnosis, providing valuable insights into feature importance and showcasing the potential of neural networks in medical applications. Our findings have implications for improving early detection and treatment strategies, ultimately contributing to improved patient outcomes. (shrink)