Deep Learning Methods in Detecting Prostate Cancer


​Contemporary approaches to prostate cancer diagnosis are fallible and inefficient, often requiring multiple specialists to confirm a single diagnosis. Computer-automated decision-making systems can reduce the rate of misdiagnosis and increase reproducibility. In particular, convolutional neural networks (CNNs) are the leading algorithm for image recognition.



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Machine Learning and the search for soft γ-ray pulsars


​A number of researchers has used machine learning technique to analyze and classify Gamma-Ray sources. However, few study has investigated whether we can have an algorithmic method to classify soft gamma-ray pulsars which have energy peaks that is under 1000 MeV. Therefore, our research focuses on using unsupervised learning machine learning to detect whether our 4FGL dataset contains different clusters. Ideally, one of the clusters should be soft gamma-ray pulsars.