Intelligent Nanotechnology for Cancer Management: Prediction, Screening, and Diagnosis

Nanotechnology and artificial intelligence are a game-changing model for oncology, facilitating unprecedented accuracy in cancer prediction, screening, and diagnosis. In-depth review: This novel in-depth literature survey consolidates the latest robust accomplishments of intelligent nanotechnology systems for diagnosing adversaries at the platform via incorporating smart nanomaterials in association with machine learning-based algorithms to facilitate precise diagnosis and thereby support personalized therapy of cancers. We focus on essential nanomaterials, such as gold nanoparticles (AuNPs), Quantum Dots (QDs), liposomes, and polymeric and carbon-based agents, which provide picomolar sensitivity in biomarker detection and further allow multimodal imaging for MRI, CT, and PET. Deep learning methods such as Convolutional Neural Networks (CNNs), vision transformers, and ensemble methods have led to diagnostic systems that could confidently attain 94–99% accuracy in cancer detection and classification for several types of cancers. Ultramodern machine learning methodologies for discovering biomarkers, integrating multi-omics data, and predicting responses to treatments translate complex heterogeneous cancer information into clinically actionable knowledge. Nonetheless, there are great obstacles to clinical translation, such as scalability of manufacturing, generalizability of algorithms between different populations, regulatory burden, and the necessity to consider biocompatibility. FDA oversight under current regulatory frameworks sets pathways for approval; however, the lack of standardization in the characterization of nanomaterials and AI model validation is still a concern. Future trends are biodegradable nanomaterials, explainable artificial intelligence, learning federations for privacy-preserving algorithm development, and combinations with immunotherapy strategies. Here, we review recent literature describing the potential of advanced nanotechnology systems for earlier cancer detection and precision medicine delivery, whereby smart nanotechnologies use bio-mimicking body signal processing capabilities to afford accurate diagnosis and tailored therapeutics (precision oncology), and we will discuss key research priorities and obstacles that require collaboration among researchers (from different disciplines) as well as with regulators, clinicians, and policy makers to achieve the full spectrum of these transformative technologies in mainstream clinical applications for cancer management.