Personalized Doctor Recommendation System

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The project has launched a personalized doctor recommendation that aims to transform patient care by using artificial intelligence (AI) to provide advice to doctors. Applications often rely on simple criteria such as proximity or accessibility, which may fail to meet the patient's physical health, preferences, and specific needs, leading to competition for the best and reducing patient satisfaction. These challenges are addressed with a smart intelligence-driven approach. Electronic health records (EHRs) include a variety of documents, including patient guides, physician records, and medical records. Artificial intelligence and machine learning models are used to analyze and process this data to create patient profiles that include medical history, treatment preferences, and other relevant factors. and first: ensuring that sensitive patient data is collected and anonymized in accordance with healthcare regulations, while maintaining data integrity. Patients are matched with the right doctor based on clinical experience, patient preferences, and past treatment results. Provide a feedback loop to continue improving recommendations based on patient satisfaction and outcomes.

Our goal is to improve patient outcomes and improve overall health by ensuring the accuracy and precision of physician recommendations. Future developments include the integration of real-time health data from impactful tools and the incorporation of predictive analytics to provide hope for patient needs. In the first step, intelligence is used to tailor doctors' recommendations to patients' conditions and preferences. The system helps improve patient care and health outcomes in many healthcare settings by improving interactions between patients and doctors.


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  • Name:
    Santhiya S
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