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AI-Powered Healthcare: Revolutionizing Patient Monitoring and Diagnosis Through Biomedical Engineering

EasyChair Preprint no. 12165

9 pagesDate: February 18, 2024


The integration of artificial intelligence (AI) in healthcare, particularly within patient monitoring and diagnosis, has spurred a revolutionary transformation in biomedical engineering. AI-powered healthcare systems leverage advanced algorithms and machine learning techniques to analyze vast amounts of patient data, facilitating early detection, accurate diagnosis, and personalized treatment plans. This paper examines the profound impact of AI on patient monitoring and diagnosis, highlighting key advancements and challenges in the field of biomedical engineering. Through the utilization of AI-driven devices and platforms, healthcare providers can remotely monitor patient vital signs, detect anomalies, and predict potential health risks in real-time. Moreover, AI algorithms can interpret medical imaging scans with unprecedented accuracy, aiding clinicians in identifying subtle abnormalities and improving diagnostic accuracy. Additionally, AIenabled decision support systems empower clinicians with actionable insights derived from comprehensive data analysis, optimizing clinical workflows and enhancing patient outcomes. The integration of AI in patient monitoring and diagnosis holds immense promise for improving healthcare delivery, enhancing patient outcomes, and advancing the field of biomedical engineering

Keyphrases: Artificial Intelligence, Biomedical Engineering, data analysis, decision, diagnosis, Healthcare, machine learning, Medical Imaging, patient monitoring, remote monitoring, support systems

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Usman Hider},
  title = {AI-Powered Healthcare: Revolutionizing Patient Monitoring and Diagnosis Through Biomedical Engineering},
  howpublished = {EasyChair Preprint no. 12165},

  year = {EasyChair, 2024}}
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