It is imperative for humans to remain as central actors in the policy- and decisionmaking processes to achieve a sustainable and inclusive society. In this article, we outline the challenges in finding better actions to realize Society 5.0 for Sustainable Development Goals through evidence-based policymaking using artificial intelligence.
The automatic, unsupervised analysis of biomedical time series is vital for diagnostic and preventive medicine, enabling fast and reliable data processing that reveals clinical insights without human intervention. This article explores and quantifies the benefits of modern deeplearning architectures of varying degrees of complexity.
Atrial fibrillation (AFib) is the most common arrhythmia, and patients with AFib have a five times higher risk for stroke. To develop an efficient and sustainable strategy for detecting undiagnosed AFib, we propose a cloud-based artificial intelligence system for arrhythmia screening, especially for AFib.
The interdisciplinary nature of sports science introduces challenges such as multifaceted data collection, accuracy in knowledge formation, and equipment usability. Artificial intelligence of things (AIoT) technology presents a feasible solution adaptable to different sports. Taking weight training as an example, we apply AIoT technology to these challenges.
The proliferation of portable devices with a wide spectrum of sensing capabilities, together with commercial availability, has made practical wearable computing applications a reality. This article focuses on efforts to make portable devices energy efficient by incorporating an intelligent dynamic energy management scheme so the overall effect on the application performance is minimal.
Dementia caregiver burden associated with patient agitation is one of the most common reasons for the institutionalization of a person with dementia. We developed an integrative sensing, analytics, modeling, and intervention system that detects early signs of agitation and notifies the caregiver to intervene before escalation.
Decision makers need credible assessments of the trustworthiness of electronic systems. Reverse engineering can provide the way forward, and the trust-assessment community should support the advancement of reversing as an engineering discipline.