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Early detection of critical illness can save lives by enabling timely medical intervention. Advances in technology have made it possible to continuously monitor vital signs and analyze data to predict health deterioration before symptoms become severe. This post explains how a new apparatus and method for monitoring vital signs work, and how they can help healthcare providers identify patients at risk of critical illness. Wearable device tracking vital signs on wrist How the

Clean water and healthy ecosystems are essential for public health. When water quality declines, it affects not only the environment but also the well-being of communities. Polluted water can carry harmful pathogens, chemicals, and toxins that lead to disease outbreaks and chronic health problems. Restoring water quality and ecosystem balance helps protect people from these risks while supporting biodiversity and sustainable resources. Clear river flowing through forest, show

Fibromyalgia has long puzzled doctors and patients alike. Characterized by widespread pain, fatigue, and cognitive difficulties, it has often been misunderstood or misdiagnosed. Recent advances in neuroimaging and biochemical research now suggest that fibromyalgia should be viewed not just as a pain syndrome but as a disorder rooted in the central nervous system (CNS). This shift in understanding could transform how fibromyalgia is diagnosed and treated. Brain scan showing al

The Quantum Leap: Understanding Quantum Support Vector Machines (QSVM) In the world of machine learning, the Support Vector Machine (SVM)  has long been a heavyweight champion for classification. It’s reliable, mathematically elegant, and handles high-dimensional data with grace. But as our datasets grow into "big data" monsters and the complexity of patterns deepens, classical computers are hitting a wall. Enter the Quantum Support Vector Machine (QSVM) —a hybrid powerhouse

Nearly 316,000 Americans are diagnosed with Breast Cancer annually. As a healthcare enthusiast and someone passionate about helping people I wanted to explore the accuracy of current Support Vector machines and its future with the combination of quantum computers. I want to see if it is an accurate method of analysis due to its high dimensionality capabilities with the kernel. The Wisconsin Breast Cancer Dataset consists of a Dimensionality of 30 which allows the need for a k