Toxaicology

This article provides an overview of the current state of artificial intelligence (AI) in the field of toxicology and medicine. It discusses the use of AI in the form of expert systems, predictive programs, computer vision, decision trees, genetic algorithms, swarm intelligence, cognitive computing, sentiment analysis, chatbots, voice recognition, recommendation systems, predictive analytics, data mining, big data, internet of things (IoT), smart cities, smart homes, autonomous vehicles, augmented reality, virtual reality, image recognition, emotion recognition, personalization, fraud detection, content generation, video analytics, medical diagnosis, energy management, supply chain management, human-robot interaction, speech synthesis, cybersecurity, blockchain, quantum computing, edge computing, cloud computing, reinforcement learning, knowledge representation, evolutionary computing, machine perception, explainable AI, ethical AI, AI policy and regulation, machine learning, deep learning, natural language processing, robotics, and automation. It also provides an overview of the current research in the field, including the use of AI for chemical safety testing, pathology, toxicogenomics, QSAR modeling, and chatGPT in medicine.