Integration of Artificial Intelligence and Computational Thinking in Lab-on-a-chip Technology for Quality Improvement in Healthcare

Abstract

The biological sciences now have a wealth of exciting prospects because of artificial intelligence (AI). For the analysis of the enormous amounts of information generated by biotechnology platforms for biological as well as biomedical applications, AI approaches can be very helpful. With advancements in controllable response chambers, high throughput arrays, and tracking devices, microfluidics generates huge quantities of data which is not always properly processed. Biotechnology research can benefit from increased clinical and analytical throughputs because of the integration of AI with microfluidics. While microfluidics improves experimental techniques and lowers costs and scales, AI technologies dramatically increase the processing of large datasets produced by multiplexed, high-throughput microfluidics. Future applications, such as high-throughput drug discovery, quick point-of-care diagnostics, and customized medicine, may all gain from the use of smart microfluidics. A summary of key advances in microfluidics integrated with AI is presented here and we discuss the possibilities for combining AI with microfluidics.