Artificial Intelligence in Medical Sensors for Clinical Decisions

Due to the limited ability of conventional methods and the limited perspective of human diagnostics, patients are often diagnosed incorrectly or at a late stage as their disease condition progresses. They may then undergo unnecessary treatments due to inaccurate diagnoses. In this Perspective, we offer a brief overview on the integration of nanotechnology-based medical sensors and artificial intelligence (AI) for advanced clinical decision support systems to help decision-makers and healthcare systems improve how they approach information, insights, and the surrounding contexts, as well as to promote the uptake of personalized medicine on an individualized basis. Relying on these milestones, wearable sensing devices could enable interactive and evolving clinical decisions that could be used for evidence-based analysis and recommendations as well as for personalized monitoring of disease progress and treatment. We present and discuss the ongoing challenges and future opportunities associated with AI-enabled medical sensors in clinical decisions.

Automated summary

Traditional diagnostic methods often lead to incorrect or delayed diagnoses for patients, but integrating nanotechnology medical sensors with artificial intelligence can improve clinical decision-making accuracy and promote personalized medicine. Wearable sensing devices enabled by AI offer interactive clinical decisions and personalized disease monitoring, presenting both challenges and opportunities in clinical decision-making.