Remote patient monitoring using artificial intelligence: Current state, applications, and challenges
The adoption of artificial intelligence (AI) in healthcare is growing rapidly. Remote patient
monitoring (RPM) is one of the common healthcare applications that assist doctors to …
monitoring (RPM) is one of the common healthcare applications that assist doctors to …
Application of artificial intelligence in wearable devices: Opportunities and challenges
D Nahavandi, R Alizadehsani, A Khosravi… - Computer Methods and …, 2022 - Elsevier
Background and objectives: Wearable technologies have added completely new and fast
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
emerging tools to the popular field of personal gadgets. Aside from being fashionable and …
Artificial intelligence and machine learning for medical imaging: A technology review
Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …
of disruptive technical advances and impressive experimental results, notably in the field of …
A Comprehensive review on AI-enabled models for Parkinson's disease diagnosis
Parkinson's disease (PD) is a devastating neurological disease that cannot be identified with
traditional plasma experiments, necessitating the development of a faster, less expensive …
traditional plasma experiments, necessitating the development of a faster, less expensive …
Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model …
A Barragán-Montero, A Bibal… - Physics in Medicine …, 2022 - iopscience.iop.org
The interest in machine learning (ML) has grown tremendously in recent years, partly due to
the performance leap that occurred with new techniques of deep learning, convolutional …
the performance leap that occurred with new techniques of deep learning, convolutional …
Bias in reinforcement learning: A review in healthcare applications
Reinforcement learning (RL) can assist in medical decision making using patient data
collected in electronic health record (EHR) systems. RL, a type of machine learning, can use …
collected in electronic health record (EHR) systems. RL, a type of machine learning, can use …
Beyond supervised learning for pervasive healthcare
The integration of machine/deep learning and sensing technologies is transforming
healthcare and medical practice. However, inherent limitations in healthcare data, namely …
healthcare and medical practice. However, inherent limitations in healthcare data, namely …
Deep reinforcement learning approaches for global public health strategies for COVID-19 pandemic
Background Unprecedented public health measures have been used during this
coronavirus 2019 (COVID-19) pandemic to control the spread of SARS-CoV-2 virus. It is a …
coronavirus 2019 (COVID-19) pandemic to control the spread of SARS-CoV-2 virus. It is a …
Rapid dynamic naturalistic monitoring of bradykinesia in Parkinson's disease using a wrist-worn accelerometer
Motor fluctuations in Parkinson's disease are characterized by unpredictability in the timing
and duration of dopaminergic therapeutic benefits on symptoms, including bradykinesia and …
and duration of dopaminergic therapeutic benefits on symptoms, including bradykinesia and …
Intelligent wearable systems: Opportunities and challenges in health and sports
Wearable devices, or wearables, designed to be attached to the human body, can gather
personalized real-time data and continuously monitor an individual's health status and …
personalized real-time data and continuously monitor an individual's health status and …