Project Title

The Rising Role of Internet Of Things in Heart Disease Diagnosis

Academic department under which the project should be listed

CCSE - Information Technology

Faculty Sponsor Name

Seyedamin Pouriyeh

Abstract (300 words maximum)

With the rate of deaths from heart disease reaching alarming numbers worldwide, specialists in the medical field have turned to innovative methods of diagnosing patients. By augmenting the currently existing concept of Internet of Things (IoT) to better suit a medical environment, the implementation of Internet of Medical Things (IoMT) arises. Utilizing a connected network of sensors allows for improved interpretation of data and therefore a more accurate diagnosis. This is achieved through the meticulous collection of interdependent data and machine learning algorithms being executed on the returned data. The sensors, either internal or external to the patient, can act as predictive assets in conjunction with other present technology. Int turn, the prospect of patient confidentiality became a major concern. As we worked through multiple scholarly studies and relevant research, we began to put together a better picture of the role IoT can provide with its predictive power in ensuring a more accurate diagnosis for patients.

Disciplines

Cardiovascular System | Diagnosis | Health Information Technology

Project Type

Poster

How will this be presented?

Yes, in person

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The Rising Role of Internet Of Things in Heart Disease Diagnosis

With the rate of deaths from heart disease reaching alarming numbers worldwide, specialists in the medical field have turned to innovative methods of diagnosing patients. By augmenting the currently existing concept of Internet of Things (IoT) to better suit a medical environment, the implementation of Internet of Medical Things (IoMT) arises. Utilizing a connected network of sensors allows for improved interpretation of data and therefore a more accurate diagnosis. This is achieved through the meticulous collection of interdependent data and machine learning algorithms being executed on the returned data. The sensors, either internal or external to the patient, can act as predictive assets in conjunction with other present technology. Int turn, the prospect of patient confidentiality became a major concern. As we worked through multiple scholarly studies and relevant research, we began to put together a better picture of the role IoT can provide with its predictive power in ensuring a more accurate diagnosis for patients.

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