In article number 2000160, Rahim Esfandyarpour and co-workers present a machine-learning-assisted-nanoparticle-printed biochip for single-cell analysis. It integrates powerful machine-learning techniques, microfluidics, and easily accessible inkjet-printing. The biochip is envisioned to have potential applications in single-cell studies, tumor heterogeneity studies, and perhaps in point-of-care diagnostics- especially in developing countries where the cost, limited infrastructures, and limited access to medical technologies are of utmost importance.
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Joshi et al. (2020) studied this question.
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