ExBEHRT: Extended Transformer for Electronic Health Records to Predict Disease Subtypes & Progressions

In this study, we introduce ExBEHRT, an extended version of BEHRT (BERT applied to electronic health records), and apply different algorithms to interpret its results. While BEHRT considers only diagnoses and patient age, we extend the feature space to several multimodal records, namely demographics, clinical characteristics, vital signs, smoking status, diagnoses, procedures, medications, and laboratory tests, by applying a novel method to unify the frequencies and temporal dimensions of the different features. We show that additional features significantly improve model performance for various downstream tasks in different diseases. To ensure robustness, we interpret model predictions using an adaptation of expected gradients, which has not been previously applied to transformers with EHR data and provides more granular interpretations than previous approaches such as feature and token importances. Furthermore, by clustering the model representations of oncology patients, we show that the model has an implicit understanding of the disease and is able to classify patients with the same cancer type into different risk groups. Given the additional features and interpretability, ExBEHRT can help make informed decisions about disease trajectories, diagnoses, and risk factors of various diseases.Comment: ICLR 2023 Workshop on Trustworthy Machine Learning for Healthcare (Website: https://sites.google.com/view/tml4h2023/accepted-papers

Light-Material Interactions Using Laser and Flash Sources for Energy Conversion and Storage Applications.

This review provides a comprehensive overview of the progress in light-material interactions (LMIs), focusing on lasers and flash lights for energy conversion and storage applications. We discuss intricate LMI parameters such as light sources, interaction time, and fluence to elucidate their importance in material processing. In addition, this study covers various light-induced photothermal and photochemical processes ranging from melting, crystallization, and ablation to doping and synthesis, which are essential for developing energy materials and devices. Finally, we present extensive energy conversion and storage applications demonstrated by LMI technologies, including energy harvesters, sensors, capacitors, and batteries. Despite the several challenges associated with LMIs, such as complex mechanisms, and high-degrees of freedom, we believe that substantial contributions and potential for the commercialization of future energy systems can be achieved by advancing optical technologies through comprehensive academic research and multidisciplinary collaborations

Magneto-Mechano-Electric (MME) Composite Devices for Energy Harvesting and Magnetic Field Sensing Applications

Magneto-mechano-electric (MME) composite devices have been used in energy harvesting and magnetic field sensing applications due to their advantages including their high-performance, simple structure, and stable properties. Recently developed MME devices can convert stray magnetic fields into electric signals, thus generating an output power of over 50 mW and detecting ultra-tiny magnetic fields below pT. These inherent outstanding properties of MME devices can enable the development of not only self-powered energy harvesters for internet of thing (IoT) systems but also ultra-sensitive magnetic field sensors for diagnosis of human bio-magnetism or others. This manuscript provides a brief overview of recently reported high-performance MME devices for energy harvesting and magnetic sensing applications

Ceramic-Based Dielectric Materials for Energy Storage Capacitor Applications

Materials offering high energy density are currently desired to meet the increasing demand for energy storage applications, such as pulsed power devices, electric vehicles, high-frequency inverters, and so on. Particularly, ceramic-based dielectric materials have received significant attention for energy storage capacitor applications due to their outstanding properties of high power density, fast charge–discharge capabilities, and excellent temperature stability relative to batteries, electrochemical capacitors, and dielectric polymers. In this paper, we present fundamental concepts for energy storage in dielectrics, key parameters, and influence factors to enhance the energy storage performance, and we also summarize the recent progress of dielectrics, such as bulk ceramics (linear dielectrics, ferroelectrics, relaxor ferroelectrics, and anti-ferroelectrics), ceramic films, and multilayer ceramic capacitors. In addition, various strategies, such as chemical modification, grain refinement/microstructure, defect engineering, phase, local structure, domain evolution, layer thickness, stability, and electrical homogeneity, are focused on the structure–property relationship on the multiscale, which has been thoroughly addressed. Moreover, this review addresses the challenges and opportunities for future dielectric materials in energy storage capacitor applications. Overall, this review provides readers with a deeper understanding of the chemical composition, physical properties, and energy storage performance in this field of energy storage ceramic materials

Perovskite Piezoelectric-Based Flexible Energy Harvesters for Self-Powered Implantable and Wearable IoT Devices

In the ongoing fourth industrial revolution, the internet of things (IoT) will play a crucial role in collecting and analyzing information related to human healthcare, public safety, environmental monitoring and home/industrial automation. Even though conventional batteries are widely used to operate IoT devices as a power source, these batteries have a drawback of limited capacity, which impedes broad commercialization of the IoT. In this regard, piezoelectric energy harvesting technology has attracted a great deal of attention because piezoelectric materials can convert electricity from mechanical and vibrational movements in the ambient environment. In particular, piezoelectric-based flexible energy harvesters can precisely harvest tiny mechanical movements of muscles and internal organs from the human body to produce electricity. These inherent properties of flexible piezoelectric harvesters make it possible to eliminate conventional batteries for lifetime extension of implantable and wearable IoTs. This paper describes the progress of piezoelectric perovskite material-based flexible energy harvesters for self-powered IoT devices for biomedical/wearable electronics over the last decade