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The Cardiac Disease Predictor: IoT and ML Driven Healthcare System

机译:心脏疾病预测因子:物联网和ML驱动的医疗保健系统

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摘要

Nowadays people suffering from diseases have dramatically shifted from communicable to non-communicable which is also quite significant in Bangladesh. Deaths due to such diseases are having a major impact on the lives of people. Among all non-communicable diseases, cardiovascular disease is highly prevalent in our country. Many people cant afford the cost of going through regular check-up. Our paper proposes a prototype which demonstrates a mechanism of identifying patients having cardiac disease. Our prototype consists of different sensor-modules to collect data e.g., Heart BPM, Cholesterol, ECG, etc. and uses a Machine Learning model to perform the classification based on the collected data. The prediction is visible to the patient instantly so that the patient can take necessary precautions beforehand. Till to date, we have managed to collect data from Heart Rate sensor, ECG sensor, Cholesterol sensor module, Blood Pressure module and currently we are working on the Glucose sensor module.
机译:如今,遭受疾病困扰的人们已从传染病急剧转变为非传染病,这在孟加拉国也相当重要。由此类疾病引起的死亡对人们的生活产生重大影响。在所有非传染性疾病中,心血管疾病在我国非常普遍。许多人负担不起定期检查的费用。我们的论文提出了一个原型,该原型演示了识别患有心脏病的患者的机制。我们的原型包含不同的传感器模块以收集数据,例如Heart BPM,胆固醇,ECG等,并使用机器学习模型基于收集的数据进行分类。该预测对患者是即时可见的,因此患者可以事先采取必要的预防措施。到目前为止,我们已经设法从心率传感器,ECG传感器,胆固醇传感器模块,血压模块收集数据,目前我们正在研究葡萄糖传感器模块。

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