From artificial intelligence to deep learning in bio-medical applications

Since their introduction in late 80s, convolutional neural networks and auto-encoder architectures have shown to be powerful for automatic feature extraction and information simplification. Using convolution kernels from image processing in 2D and 3D spaces for the stage by stage features retrieval processes, allows the architecture to be as flexible as the designer wants, considering that this is not a lucky fact. With the recent ten years of technological progress now we can compute and train those architectures and they have faced so many challenges for applications originating the most famous CNN architectures. This chapter presents an author position related to the artificial intelligence field and machine learning/deep learning appearance in the scientific world scene describing hastily the basis for each one and later, focusing on medical applications most of the socialized on the Annual IEEE Engineering in Medicine and Biology Society conference held in Hawaii in July 2018. While addressing the medical applications from cardiovascular to cancer diagnosis, we will briefly describe the architectures and discuss some features. Finally, we will present a contribution to the deep learning by introducing a new architecture called Convolutional Laguerre-Gauss Network with a kernel based on a spiral phase function ranging from 0 to 2p and a toroidal amplitude band-pass filter, known as the Laguerre-Gauss transform. © Springer Nature Switzerland AG 2020

The effect of ethanolic extract of Thymus kotschyanus on cancer cell growth in vitro and depression-like behavior in the mouse

Cancer and depression are known as two of the most debilitating disease and disorder increasing evidence suggest an urgent need for new therapeutic agents with lower toxicity and high efficacy. Some Thyme species extracts have remarkably been shown to positively affect depression and cancer cells. In the present study, we investigated the effect of Thymus kotschyanus on depression and cancer cells. To this end, in experiment 1, NMRI mice were treated orally with the ethanolic extract of T. kotschyanus (50, 150 and 250 mg/ml) for seven days and then depression-like behavior was measured by Forced Swim Test (FST) and Tail Suspension Test (TST). In experiment 2, the pharmacological effect of the extract on the lung (A549) and cervical (Hela) cancer cell lines was also evaluated by MTT (3-(4,5-Dimethylthiazol-2-Yl)-2,5-Diphenyltetrazolium Bromide) in various concentration_(10, 5, 2.5, 1.25, 0.63, 0.31, 0.15 and 0.08 mg/ml). The results indicated that T. kotschyanus extract treatment (150 and 250 mg/kg) decreased depression-like behavior in the FST and TST tests in adult mice. Moreover, the treatment inhibited cancer cell growth and viability in a dose and time-dependent manner. Collectively these findings suggest that T. kotschyanus have antidepressant and anticancer effects