This systematic literature review explores the intersection of neuroscience and deep learning in the context of decoding motor imagery Electroencephalogram (EEG) signals to enhance the quality of life for individuals with motor disabilities. Currently, the most used non-invasive method for measuring brain activity is the EEG, due to its high temporal resolution, user-friendliness, and safety. A Brain Computer Interface (BCI) framework can be made using these signals which can provide a new communication channel to people that are suffering from motor disabilities or other neurological disorders. However, implementing EEG-based BCI systems in real-world scenarios for motor imagery recognition presents challenges, primarily due to the inherent variability among individuals and low signal-to-noise ratio (SNR) of EEG signals. To assist researchers in navigating this complex problem, a comprehensive review article is presented, summarizing the key findings from relevant studies since 2017. This review primarily focuses on the datasets, preprocessing methods, feature extraction techniques, and deep learning models employed by various researchers. This review aims to contribute valuable insights and serve as a resource for researchers, practitioners, and enthusiasts interested in the combination of neuroscience and deep learning, ultimately hoping to contribute to advancements that bridge the gap between the human mind and machine interfaces.
Primary adrenal lymphomas (PAL) are rare occurrences with only less than 150 cases reported in the literature. Two-thirds of these cases were reported in the last decade due to the advancements in imaging techniques and immunohistochemistry. The non-specific signs and symptoms have resulted in a delayed onset of symptoms and diagnosis of these tumors. Reports of the results of chemotherapy are not gratifying, and most patients die within one year of the diagnosis. We report a 65-year-old male with adrenal non-Hodgkin's lymphoma (NHL), who presented with hypercalcemia and renal failure. We reviewed all adrenal NHL cases presented with hypercalcemia and attempted to comprehend its etiology and overall survival effect.