The electrochemical biosensors are a class of biosensors which convert biological
information such as analyte concentration that is a biological recognition element …

Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis.
Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved …

Advances in technology have been able to affect all aspects of human life. For example, the
use of technology in medicine has made significant contributions to human society. In this …

Convolutional neural networks, are one of the most representative deep learning models.
CNNs were extensively used in many aspects of medical image analysis, allowing for great …

Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis,
treatment planning, and treatment outcome evaluation. Build upon successful deep learning …

The successful early diagnosis of brain tumors plays a major role in improving the treatment
outcomes and thus improving patient survival. Manually evaluating the numerous magnetic …

Accurate automatic algorithms for the segmentation of brain tumours have the potential of
improving disease diagnosis, treatment planning, as well as enabling large-scale studies of …

The brain tumor is considered the deadly disease of the century. At present, neuroscience
and artificial intelligence conspire in the timely delineation, detection, and classification of …

In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation
that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual …

Manual segmentation of the brain tumors for cancer diagnosis from MRI images is a difficult,
tedious, and time-consuming task. The accuracy and the robustness of brain tumor …