AI-Based Prediction of Clinical Events Among Hemodialysis Patients Using Non-Contact Sensor Data

Read the full article here This article presents an example of how artificial intelligence techniques can be applied to predict clinical events among haemodialysis patients.

Non-contact sensors are gaining popularity in clinical settings to monitor the vital parameters of patients. In this study, the study group used a non-contact sensor device to monitor vital parameters like the heart rate, respiration rate, and heart rate variability of hemodialysis (HD) patients for a period of 23 weeks during their HD sessions.The final findings point towards the novel use of non-contact sensors in clinical settings to monitor the vital parameters of patients and the further development of early warning solutions using artificial intelligence (AI) for the prediction of clinical events. These models could assist healthcare professionals in taking decisions and designing better care plans for patients by early detecting changes to vital parameters.

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This article is from the free online course:

Artificial Intelligence for Healthcare: Opportunities and Challenges

Taipei Medical University