癌症是全球主要死亡原因之一，早期检测和准确诊断对于有效治疗和改善患者预后至关重要。近年来，机器学习（ML）作为一种强大的癌症检测工具崭露头角，能够开发创新算法，分析大量数据并提供准确的预测。本综述旨在全面介绍用于癌症检测的各种ML算法和技术，着重介绍该领域的最新进展、挑战和未来发展方向。主要挑战在于寻找一种安全、可审计和可靠的基础科学出版物分析方法。食品污染物分析是一种测试食品产品以确定和量化有害物质或污染物存在的过程。这些物质可以包括细菌、病毒、毒素、农药、重金属、过敏原和其他化学残留物。机器学习（ML）和人工智能（A.I）作为一种有着很大潜力的方法，被提出可以提取具有高度有效性的信息，这些信息可能在传统分析技术中被忽视，并且具有广泛的应用研究领域。A.I技术在元光学中的应用未来可以将光学器件和系统发展到更高的水平。此外，机器学习（M.L.）和人工智能（A.I.）在纳米材料在环境和人类健康研究中的安全评估方面扮演着重要角色。此外，并且确信了机器学习在设计具有更高分辨率和检测性能的等离子敏感传感器的各种应用中的益处。© 2023. Springer Nature Limited.

Cancer is one of the leading causes of death worldwide, making early detection and accurate diagnosis critical for effective treatment and improved patient outcomes. In recent years, machine learning (ML) has emerged as a powerful tool for cancer detection, enabling the development of innovative algorithms that can analyze vast amounts of data and provide accurate predictions. This review paper aims to provide a comprehensive overview of the various ML algorithms and techniques employed for cancer detection, highlighting recent advancements, challenges, and future directions in this field. The main challenge is finding a safe, auditable and reliable analysis method for fundamental scientific publication. Food contaminant analysis is a process of testing food products to identify and quantify the presence of harmful substances or contaminants. These substances can include bacteria, viruses, toxins, pesticides, heavy metals, allergens, and other chemical residues. Machine learning (ML) and artificial intelligence (A.I) proposed as a promising method that possesses excellent potential to extract information with high validity that may be overlooked with conventional analysis techniques and for its capability in a wide range of investigations. A.I technology used in meta-optics can develop optical devices and systems to a higher level in future. Furthermore (M.L.) and (A.I.) play key roles as a health Approach for nano materials NMs safety assessment in environment and human health research. Beside, benefits of ML in design of plasmonic sensors for different applications with improved resolution and detection are convinced.© 2023. Springer Nature Limited.