Detection and Analysis of Mental Health Illness using social media

Recently social media has been a widely used network that connects people around the world. Not only this but people sharing their life events, thoughts through posts, status updates all gather up as a big data resource. This resource is helpful in conducting various researches, analyses including big data and machine learning. In this study, we analyzed six mental health issues using Reddit’s data. The data obtained summarizes; Depression, Anxiety, Bipolar, Bipolar Disorder, Schizophrenia, Autism and Mental Health which is a general class which discusses mental health. Experimentation is done using various deep learning and NLP techniques applied for classification such as Convolutional Neural Network, Long-short term memory network, Gated Recurrent Unit, Bi- Long-short term memory network and Bi-Gated Recurrent Unit. In addition to these traditional techniques, pre-trained BERT model and …

An Automated Teeth Lesion Diagnosis based on deep learning

A pipeline based on context-aware light-weight transformers with the goal of improving image quality without sacrificing the naturalness of the image, as well as reducing the inference time and size of the model. In this study, we trained a deep network-based transformer model on two standard datasets, i.e., Large-Scale Underwater Image (LSUI) and Underwater Image Enhancement Benchmark Dataset (UIEB), so that the network becomes more generalized, which subsequently improved the performance. Our real-time underwater image enhancement system shows superior results on edge devices. Also, we provide a comparison with other transformer-based methods.

Enhanced Expert Systems for Medical Diagnostic using Data Mining

Machine learning algorithms have great potential for exploring the hidden patterns in the data sets of the medical domain. These patterns can be utilized for clinical diagnosis. Since medical diagnostic decision support systems have become more popular in clinical routine, it is critical to decide the best model to provide reliable machine learning techniques in diagnostic problems. The purpose of my research thesis is […]