Chemometrics play a critical role in biosensorsbased detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, especially deep learning, which is famous for image analysis, facial recognition, and speech recognition, has remained relatively elusive to the biosensor community. Herein, how ML can be beneficial to biosensors is systematically discussed. The advantages and drawbacks of most popular ML algorithms are summarized on the basis of sensing data analysis. Specially, deep learning methods such as convolutional neural network (CNN) and recurrent neural network (RNN) are emphasized. Diverse ML-assisted electrochemical biosensors, wearable electronics, SERS and other spectra-based biosensors, fluorescence biosensors and colorimetric biosensors are comprehensively discussed. Furthermore, biosensor networks and multibiosensor data fusion are introduced. This review will nicely bridge ML with biosensors, and greatly expand chemometrics for detection, analysis, and diagnosis.

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Cancer is a dreadful disease with a high mortality rate, and it has become more and more prevalent worldwide. Early diagnosis, prognosis and treatment monitoring with robust and non-invasive tools will potentially be the future focus. Electrochemical biosensor can be a strong candidate for cancer theranostics owing to their advantage of ultra-sensitivity, high selectivity, low cost, quick readout, and simplicity. Furthermore, electrochemical biosensors are easier to be miniaturized and mass fabricated, which grant them a better fit for point-of-care applications. In this review, various electrochemical measurement methods, bioreceptor surface, signal generation and amplification, integration of electrochemical sensors in microfluidic chips were summarized. Especially, multiplexed and ratiometric electrochemical biosensor were emphasized in cancer biomarkers detection. Then, measurement and analysis of cancers based on electrochemical biosensors in molecular level (DNA, RNA, and protein), organelle level (exosomes), cell level (cell counting, phenotypic and metabolism analysis, drug sensitivity monitoring) were comprehensively discussed. As a new research trend, the integration of electrochemical biosensors in cancer-on-a-chip has been highlighted. In brief, we present an overall review of current advances in cancers measurement and analysis using electrochemical biosensors. Finally, the current challenges and future directions were discussed.

Owing to their merits of simple, fast, sensitive, and low cost, electrochemical biosensors have been widely used for the diagnosis of infectious diseases. As a critical element, the receptor determines the selectivity, stability, and accuracy of the electrochemical biosensors. Molecularly imprinted polymers (MIPs) and surface imprinted polymers (SIPs) have great potential to be robust artificial receptors. Therefore, extensive studies have been reported to develop MIPs/SIPs for the detection of infectious diseases with high selectivity and reliability. In this review, we discuss mechanisms of recognition events between imprinted polymers with different biomarkers, such as signaling molecules, microbial toxins, viruses, and bacterial and fungal cells. Then, various preparation methods of MIPs/SIPs for electrochemical biosensors are summarized. Especially, the methods of electropolymerization and micro-contact imprinting are emphasized. Furthermore, applications of MIPs/SIPs based electrochemical biosensors for infectious disease detection are highlighted. At last, challenges and perspectives are discussed.

Graphical abstract Laser-induced graphene (LIG) is a class of three-dimensional (3D) porous carbon nanomaterial. It can be prepared by direct laser writing on some polymer materials in the air. Because of its features of simplicity, fast production, and excellent physicochemical properties, it was widely used in medical sensing devices. This minireview gives an overview of the characteristics of LIG and LIG-driven sensors. Various methods for preparing graphene were compared and discussed. The applications of the LIG in biochemical sensors for ions, small molecules, microRNA, protein, and cell detection were highlighted. LIG-based physical physiological sensors and wearable electronics for medical applications were also included. Finally, our insights into current challenges and prospects for LIG-based medical sensing devices were presented.