A Low-Power Analog Processor-in-Memory-Based Convolutional Neural Network for Biosensor Applications

Leveraging the Academic Artificial Intelligence Silecosystem to Advance the Community Oncology Enterprise

Over the last 75 years, artificial intelligence has evolved from a theoretical concept and novel paradigm describing the role that computers might play in our society to a tool with which we daily engage. In this review, we describe AI in terms of its constituent elements, the synthesis of which we refer to as the AI Silecosystem. Herein, we provide an historical perspective of the evolution of the AI Silecosystem, conceptualized and summarized as a Kuhnian paradigm. This manuscript focuses on the role that the AI Silecosystem plays in oncology and its emerging importance in the care of the community oncology patient. We observe that this important role arises out of a unique alliance between the academic oncology enterprise and community oncology practices. We provide evidence of this alliance by illustrating the practical establishment of the AI Silecosystem at the City of Hope Comprehensive Cancer Center and its team utilization by community oncology providers.

Where Microneedle Meets Biomarkers: Futuristic Application for Diagnosing and Monitoring Localized External Organ Diseases

Extracellular tissue fluids are interesting biomatrices that have recently attracted scientists' interest. Many significant biomarkers for localized external organ diseases have been isolated from this biofluid. In the diagnostic and disease monitoring context, measuring biochemical entities from the fluids surrounding the diseased tissues may give more important clinical value than measuring them at a systemic level. Despite all these facts, pushing tissue fluid-based diagnosis and monitoring forward to clinical settings faces one major problem: its accessibility. Most extracellular tissue fluid, such as interstitial fluid (ISF), is abundant but hard to collect, and the currently available technologies are invasive and expensive. This is where novel microneedle technology can help tackle this significant obstacle. The ability of microneedle technology to minimally invasively access tissue fluid-containing biomarkers will enable ISF and other tissue fluid utilization in the clinical diagnosis and monitoring of localized diseases. This review attempts to present the current pursuit of the application of microneedle systems as a diagnostic and monitoring platform, along with the recent progress of biomarker detection in diagnosing and monitoring localized external organ diseases. Then, the potential use of various microneedles in future clinical diagnostics and monitoring of localized diseases is discussed by presenting the currently studied cases.

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning

The ability to interpret information through automatic sensors is one of the most important pillars of modern technology. In particular, the potential of biosensors has been used to evaluate biological information of living organisms, and to detect danger or predict urgent situations in a battlefield, as in the invasion of SARS-CoV-2 in this era. This work is devoted to describing a panoramic overview of optical biosensors that can be improved by the assistance of nonlinear optics and machine learning methods. Optical biosensors have demonstrated their effectiveness in detecting a diverse range of viruses. Specifically, the SARS-CoV-2 virus has generated disturbance all over the world, and biosensors have emerged as a key for providing an analysis based on physical and chemical phenomena. In this perspective, we highlight how multiphoton interactions can be responsible for an enhancement in sensibility exhibited by biosensors. The nonlinear optical effects open up a series of options to expand the applications of optical biosensors. Nonlinearities together with computer tools are suitable for the identification of complex low-dimensional agents. Machine learning methods can approximate functions to reveal patterns in the detection of dynamic objects in the human body and determine viruses, harmful entities, or strange kinetics in cells.