Deep Neural Networks and Their Role in the Medical and Technological Fields<br />Introduction<br />In recent years, the world has witnessed a major technological revolution thanks to artificial intelligence, with Deep Neural Networks (DNNs) being one of its most influential and prominent tools. This technique is inspired by the way the human brain works, allowing computer systems to “learn” from data and process information intelligently. As a result, DNNs have become a cornerstone in many applications in both medical and technological domains.<br /><br />What Are Deep Neural Networks?<br />Deep neural networks are an advanced type of artificial neural network composed of several successive layers of neurons, including:<br /><br />Input Layer<br /><br />Multiple Hidden Layers<br /><br />Output Layer<br /><br />Each layer learns a complex representation of the data and passes the results to the next layer, enabling the system to recognize patterns and make decisions without direct human intervention.<br /><br />The Role of Deep Neural Networks in the Medical Field<br />High-Accuracy Disease Diagnosis<br />Deep neural networks can be trained on medical images (e.g., X-rays or MRI scans) to diagnose diseases such as cancer, heart conditions, and eye disorders, often with accuracy that surpasses human doctors.<br /><br />Medical Image Analysis<br />DNNs are used for automatic detection of tumors, internal bleeding, and tissue damage, speeding up diagnosis and reducing human error.<br /><br />Health Condition Prediction<br />Deep models can predict the deterioration of a patient's condition based on vital signs and medical history, enabling proactive intervention.<br /><br />Assistance in Robotic Surgery<br />Neural networks enhance precision in robotic surgery by enabling quick decision-making and improving operational accuracy.<br /><br />Electronic Medical Records Analysis<br />DNNs help classify and analyze massive volumes of patient data to extract crucial insights and improve healthcare quality.<br /><br />The Role of Deep Neural Networks in the Technological Field<br />Image and Voice Recognition<br />Major companies like Google and Apple use neural networks for technologies such as facial recognition and intelligent voice assistants (e.g., Siri, Alexa).<br /><br />Self-Driving Cars<br />DNNs process sensor and camera data in autonomous vehicles to make real-time decisions like braking or lane changes.<br /><br />Cybersecurity<br />DNNs assist in detecting cyberattacks and analyzing user behavior to automatically identify suspicious activities.<br /><br />Big Data Analysis<br />In the era of big data, deep networks help uncover hidden patterns and support real-time intelligent decision-making.<br /><br />Machine Translation and Natural Language Processing<br />DNNs enhance translation accuracy and human language understanding, as seen in systems like NLP programs <br /><br />Al-Mustaqbal University: The Number One University in Iraq.<br /><br /><br /><br /><br /><br /><br /><br /><br /><br />