Flexible and wearable biosensors are the next‐generation healthcare devices that can
efficiently monitor human health conditions in day‐to‐day life. Moreover, the rapid growth …

The success of machine learning (ML) techniques in the formerly difficult areas of data
analysis and pattern extraction has led to their widespread incorporation into various …

Machine learning (ML) has succeeded in improving our daily routines by enabling
automation and improved decision making in a variety of industries such as healthcare …

Edge AI, an interdisciplinary technology that enables distributed intelligence with edge
devices, is quickly becoming a critical component in early health prediction. Edge AI …

Machine Learning (ML) and Deep Learning (DL) are derivatives of Artificial Intelligence (AI)
that have already demonstrated their effectiveness in a variety of domains, including …

Cardiovascular diseases present a significant global health challenge that emphasizes the
critical need for developing accurate and more effective detection methods. Several studies …

When children are discharged from the hospital after surgery, their caregivers often rely on
subjective assessments (eg, appetite, fatigue) to monitor postoperative recovery as objective …

Cardiovascular diseases (CVDs) remain a leading cause of morbidity and mortality
worldwide. Effective prevention and management strategies are essential to reduce the …

Introduction The increasing availability of data and computing power has made machine
learning (ML) a viable approach to faster, more efficient healthcare delivery. Methods A …

Real-time monitoring of heartbeat signals using multimode fiber optic microvibration sensing
technology is crucial for diagnosing cardiovascular diseases, but the heartbeat signals are …