European Journal of Biomedical and Pharmaceutical Sciences

INTEGRATING MACHINE LEARNING, DEEP LEARNING, AND IOT IN RECENT HEALTHCARE

*Njood Daifallah Faisal Aldughmi, Eman Kamal Lutfi Taher, Anwar Amin Ali Albtoush,
Ayat Ahmad Mohammad Nawasreh, Saja Eid Suliman Asharari

ABSTRACT

The combination of Machine Learning (ML), Deep Learning (DL), and the Internet of Things (IoT) in biomedical engineering is transforming healthcare by providing innovative solutions for diagnosis, treatment, and patient care. Recent high-tech medical devices capture real-time patient data, including vital signs and environmental conditions, which ML algorithms and DL algorithms evaluate to detect trends, forecast outcomes, and support clinical decision-making. This integration of algorithms, biomedical sensors, and processing platforms enhances the accuracy of patient diagnoses and doctors’ decisions while reducing morbidity and mortality. However, this integration enables accurate prediction of results, early disease detection, proactive management of chronic conditions, and improved treatment procedures. The combination of these technologies into medical instruments, such as wearable health trackers, implantable sensors, and smart diagnostic implements, proposes encouraging opportunities for developing patient outcomes, decreasing healthcare costs, and addressing the cumulative request for healthcare facilities.

Keywords: Machine Learning, Deep Learning, Internet of Things, Biomedical Engineering, Healthcare Solutions.