Machine Learning and Artificial Intelligence for Next-Generation Intelligent Data Analytics: A Cross-Domain Review of Healthcare, Cybersecurity, Blockchain, and Supply Chains

Engineering notes

Key topics: autonomous driving, reinforcement learning, prediction. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

In the rapidly evolving landscape of today's world, Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing intelligent data analytics, empowering decision-making across various sectors with enhanced data-driven insights. This review covers concepts from the foundation up, next-generation analytic techniques, cross-domain applications and some key challenges as well as future directions. Supervised, unsupervised and reinforcement learning are some of the core ML approaches which enable predictive and adaptive systems. Real-time analytics, edge computing, and explainable AI are some of the emerging technologies that improve efficiency and transparency. Healthcare, cybersecurity, blockchain and supply chain management are all examples of areas where we see considerable advances in prediction, security, and optimization. But data challenges like privacy, quality, data scalability, and ethical issues remain. The future of federated learning, quantum computing, and autonomous systems, among other trends, holds the potential of continued innovation, propelling intelligent, secure, and scalable analytics ecosystems across the globe.

Links and sources

• PDF from original source

Comments