AI-guided SWIR smart garment for breast interstitial fluid surveillance: A literature-informed translational framework for wearable molecular–thermal breast health monitoring

BackgroundCurrent breast cancer screening approaches rely mainly on periodic imaging and circulating biomarkers, which may not fully capture localized molecular and physiological alterations during early tumorigenesis.ObjectiveTo propose a literature-informed translational framework for an AI-guided SWIR smart garment integrating molecular and thermal sensing technologies for longitudinal breast health surveillance.MethodsThe proposed breast-conformal wearable platform integrates dissolvable microneedle-mediated interstitial fluid (ISF) sampling, ligand-functionalized short-wave infrared (SWIR)-emitting rare-earth nanoparticles, thermal microsensors, and artificial intelligence (AI)-assisted multimodal analysis.ResultsThe resulting framework proposes an integrated wearable system capable of potentially accessing localized breast ISF, generating biomarker-responsive optical signals, and monitoring regional temperature variations and bilateral thermal asymmetry. AI-assisted analysis is envisioned to combine molecular, thermal, and longitudinal measurements to establish individualized physiological baselines, recognize persistent deviations, and support clinical follow-up decisions. These capabilities represent proposed functional objectives rather than experimentally demonstrated outcomes, and their analytical and clinical performance remains unvalidated.ConclusionThe proposed platform represents a potential adjunctive approach for longitudinal breast health monitoring rather than a replacement for established screening and diagnostic methods. Further investigations are required to evaluate its feasibility, safety, analytical performance, reproducibility, data governance, and clinical relevance through sensor characterization, preclinical testing, and exploratory clinical studies.