Revolutionizing Healthcare: Disease and Symptom-based Hospital Prediction using Machine Learning

Authors: B.L. Gunjal, Vitthal Kolhe, Mahesh Tawar, Saurav Shimpi, Om Narhare

Country: India

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Abstract: The System represents a cutting-edge initiative poised to transform healthcare delivery. With its seven integral components, it addresses the myriad challenges faced by both patients and healthcare providers. Beginning with symptom analysis and disease prediction, it em powers patients with valuable insights into their health concerns. The system simplifies the daunting task of choosing the right healthcare facility with its hospital prediction feature. Ad ditionally, it streamlines the appointment scheduling process, ensuring patients can easily book appointments with their chosen healthcare professionals. Moreover, the resource allocation component optimizes the utilization of medical instruments and doctor availability. Further more, the system enables personalized interactions between patients and healthcare providers, fostering stronger patient-provider relationships and individualized treatment plans. Finally, the feedback and review system promotes continuous service improvement, creating a feed back loop that ensures patients’ voices are heard and acted upon. This integrated healthcare management system aspires to elevate the quality of healthcare services, delivering a patient centered approach that improves patient outcomes and provider efficiency in an ever-evolving healthcare landscape.

Keywords: Healthcare Delivery Transformation, Symptom Analysis, Disease Prediction

Paper Id: 230614

Published On: 2024-04-27

Published In: Volume 12, Issue 2, March-April 2024

Cite This: Revolutionizing Healthcare: Disease and Symptom-based Hospital Prediction using Machine Learning - B.L. Gunjal, Vitthal Kolhe, Mahesh Tawar, Saurav Shimpi, Om Narhare - IJIRMPS Volume 12, Issue 2, March-April 2024.

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