David Keeley's research while affiliated with New Mexico State University and other places

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Publication (1)

Distribution of heart rate data for the MIT-BIH database patient
Detected anomalies (each shown as a red x) for the local outlier factor...
a Detected anomalies (each shown as a red x) for the random and...
Detected anomalies (each shown as a red x) for the local outlier factor...
Healthcare and anomaly detection: using machine learning to predict anomalies in heart rate data
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  • Mar 2021
The application of machine learning algorithms to healthcare data can enhance patient care while also reducing healthcare worker cognitive load. These algorithms can be used to detect anomalous physiological readings, potentially leading to expedited emergency response or new knowledge about the development of a health condition. However, while the...
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Citations

... Gogoi et al. [14] proposed a breast abnormal detection method through statistical feature analysis using infrared thermograms. Šabić et al. [15] developed a machine-learning-based healthcare and anomaly detection method to predict anomalies in heart rate data, which can enhance patient care while also reducing healthcare workers' cognitive load. Their findings demonstrated the advantages of the local outlier factor (LOF) in the task of heart rate prediction. ...
Reference: Long-Short-Term-Memory-Based Deep Stacked Sequence-to-Sequence Autoencoder for Health Prediction of Industrial Workers in Closed Environments Based on Wearable Devices
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