Artificial Intelligence in Malaria Diagnostics

Abstract

Apart from the ongoing global pandemic of coronavirus disease 2019 (COVID-19), malaria remains one of the major threats to human health. Every year, about 200 million new cases of malaria are diagnosed worldwide, resulting in more than 400,000 deaths. Timely diagnosis of malaria is critical to reducing its transmission and mortality. In order to improve the diagnosis level of malaria in remote rural areas, artificial intelligence models based on deep learning algorithms are gradually applied to the microscope for the malaria detection in blood smears. This review outlines the principles of such technologies, introduces the latest progress of current artificial intelligence models in microscopy for malaria, and looks forward to the application prospects of deep learning and smart phone technology in the field of malaria diagnosis.

SemiSynBio: A new era for neuromorphic computing

“…Biocomputing is expected to become widespread in many fields, such as DNA data storage and encryption, medical diagnosis, drug delivery, and intelligent biosensor [ [54] , [55] , [56] , [57] , [58] , [59] , [60] , [61] , [62] , [63] ]. Inspired by the computational power of “DNA strand displacement,” Wang et al enhanced DNA storage with parallel “in-memory” molecular computation using strand displacement reactions to algorithmically modify data, showing that large cascades involving 244 strand exchanges can use naturally occurring DNA sequence from M13 bacteriophage, possibly expanding computational capacity and reducing costs [ 64 ].…”