Artificial intelligence (AI) is one of the most advanced technologies of the modern era, and it has begun to make a huge impact in many areas, including healthcare. This scientific article aims to explore how artificial intelligence can be used in fracture detection, focusing on the methods and techniques used, as well as the benefits and challenges of this application.<br /><br />Methods and techniques used in fracture detection<br />Analysis of medical images using machine learning:<br />Machine learning algorithms are used to analyze medical images such as X-rays, magnetic resonance imaging (MRI), computed tomography (CT). These algorithms can be trained on huge data sets to accurately determine fractions.<br /><br />Deep Learning (Deep Learning):<br />Deep learning networks, such as convolutional neural networks (CNNs), rely on multiple layers to analyze images and extract patterns from them. These networks are trained on a large number of images to develop a model capable of recognizing fractures with high accuracy.<br /><br />Artificial intelligence as a support tool for doctors:<br />Artificial intelligence systems can act as an assistant to doctors by providing preliminary analyzes of medical images. This can help speed up the diagnostic process and reduce human errors.<br /><br />The benefits of using artificial intelligence in fracture detection<br />Increased diagnostic accuracy:<br />Artificial intelligence helps improve diagnostic accuracy by detecting fractures that may be difficult for doctors to see with the naked eye.<br /><br />Speeding up the diagnostic process:<br />Artificial intelligence systems can analyze medical images extremely quickly, allowing doctors to provide the right treatment in a shorter time.<br /><br />Reduce human errors:<br />Relying on artificial intelligence reduces the likelihood of human errors during the diagnostic process, which improves the quality of health care.<br /><br />Access to remote areas:<br />Artificial intelligence technologies can be used in regions with a shortage of specialist doctors, providing high-quality medical services to these regions.<br /><br />Challenges of using artificial intelligence in medical diagnostics<br />Privacy and security issues:<br />The use of artificial intelligence requires access to large amounts of medical data, which raises issues about the privacy and security of this data.<br /><br />Development and implementation cost:<br />The cost of developing and implementing AI systems can be high, which is a challenge for health institutions with limited resources.<br /><br />The need for human supervision:<br />Despite the many benefits, it is not possible to fully rely on artificial intelligence, since human experience remains essential in the process of medical diagnosis.