This feature release adds new social media icons for 2024 and makes dark mode available to everyone.
Lots of things have changed in the world of social media since the last release. To bring Hydejack up to date, the default logo for Twitter has changed:
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Heart disease is the leading cause of death globally, causing many millions of deaths each year. I created a custom deep convolutional neural network that can classify heartbeat sounds as normal or abnormal with an accuracy of 98%. I also developed a smartphone app that allows users to screen their own heart sounds for abnormality. This technology serves as a preliminary screening to test if you have a heart problem and if you need to see a healthcare professional. I hope that this project can reduce the incidence of undiagnosed heart problems.
Heart diseases are a major public health problem worldwide. According to the World Health Organization (WHO), cardiovascular diseases are the leading cause of death globally, taking around 17.9 million lives each year. Thus, early detection of heart problems is crucial for improving patient outcomes. To detect heart problems, heart sounds or phonocardiograms (PCGs) can be manually heard and analyzed by trained experts using stethoscopes, in a process called cardiac auscultation. Abnormal heart sounds such as heart murmurs can be indicative of a variety of heart diseases, such as mitral regurgitation, aortic sclerosis and more. Therefore, analyzing heart sounds can provide valuable information for the diagnosis of heart diseases. In this project, I aim to develop a system to automatically classify heart sounds as normal or abnormal at very high accuracy. I model this as an image classification problem by converting audio samples into a visual representation using features such as Mel Frequency Cepstral Coefficients. This transformation allows me to use a convolutional neural network (CNN) based design, which is known to be highly accurate at image classification tasks. My model achieves a test accuracy of around 98% after being trained on the heart sounds from the publicly available PhysioNet/CinC Challenge 2016 dataset. We further develop a smartphone app that uses this model to classify new heart sound data. My research paves the way for low-cost and scalable early detection of heart disease, potentially preventing deaths due to undiagnosed heart conditions.
Version 9 is the most complete version of Hydejack yet. Modernized design, big headlines, and big new features.
Version 9 is the most complete version of Hydejack yet.
A page showing Hydejack-specific markdown content.
Hydejack offers a few additional features to markup your markdown. Don’t worry, these are merely CSS classes added with kramdown’s {:...} syntax, so that your content remains compatible with other Jekyll themes.
A page showing how regular markdown content is styled in Hydejack.
There should be whitespace between paragraphs. We recommend including a README, or a file with information about your project.
Howdy! This is an example blog post that shows several types of HTML content supported in this theme.
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