ABSTRACT
Soft computing tools provide a solution toward complicated real-life limitations using approximation models such as fuzzy logic, evolutionary computation, chaos theory, artificial neural network, probabilistic approximation, etc. The corroboration between nanomagnetism and soft computing offers a bridge to exploit advanced nanomagnetic devices in the biomedical field. In medical image processing, advanced medical imaging techniques such as multidetector computed tomography (MDCT) and magnetic resonance (MR) imaging affirm a larger number of complex data, which results huge challenges for human intelligence. In this aspect, soft computing is found as an effectual technique to control unpredictable inherence in observed data of imaging. Moreover, nanomagnetic spintronic devices, used in various applications (such as biomedical imaging, diagnostic and cytometric applications, magnetoresistive sensors, etc.), are found as a suitable candidate for imitating artificial neurons and artificial synapses due to their enhanced spin nonlinearity and nonvolatility of information. As a consequence, the hardware implementation of soft computing such as artificial neural network in spintronic devices can overcome the existing lacuna of nanomagnetic devices. We represent here a systematic review on contemporary efforts for nanomagnetic devices coupled with soft computing for efficient applicability toward the biomedical field. The primary focus is to explore background understanding, motivation toward applications and an elucidation to the techniques used in the development of soft computing tools during device fabrication. This comprehensive study infers that the interface between nanomagnetism and intelligent systems techniques is still obscure. The necessity to standardize the computational and intelligent devices engineering technology used in nano-magnetism, therefore, emerges, which will provide a promising pathway for the development of advanced biomedical technologies.
