Skin cancer is a widespread and potentially deadly condition. It is crucial to catch it early for successful treatment. Skin cancer makes up 1 in 5 of all cancer cases worldwide. Melanoma alone causes over 60, 000 deaths each year. This highlights the need for effective early detection methods. Traditional skin cancer screening by doctors is time-consuming and cos...

Medical image classification has seen a huge boost from deep convolutional neural networks (CNNs). These networks are like super-smart detectors that can spot patterns in medical images. However, there are two big hurdles to overcome. First, medical data from different places isn't always the same. This is because each hospital or clinic might have different types of...

Imagine if detecting skin cancer could be as simple as snapping a picture. Scientists are working on just that! They're using a special kind of computer program called convolutional neural networks (CNNs), and these aren't your average programs. They're like super-smart detectives that can spot patterns in images, like skin lesions. But how do they make these progra...

Researchers have been using special maps called saliency maps to understand why certain AI models make specific decisions about glaucoma. They trained these AI models, called convolutional neural networks, to diagnose glaucoma using pictures of the eye's fundus, which is the inner lining of the eye. But instead of using full images, they simplified things by only sho...

Imagine having the ability to identify sports activities just by using basic motion data. This is exactly what a new method called Human Activity Recognition (HAR) does. By using sensors and special learning algorithms, HAR can tell the difference between various sports activities with impressive accuracy. This helps everyone, from kids to adults. The future looks br...