Smart Symptom-to-Care System Using AI and Machine Learning: Intelligent Health Diagnosis and Personalized Medical Guidance for Early Disease Detection

In an increasingly digital world, individuals often seek online health guidance and face overwhelming, unreliable, and complex information. To address this, Smart Symptom-to-Care AI has been developed as a comprehensive and trustworthy web application serving as the first point of contact for personal health inquiries. Leveraging the advanced reasoning and structured data capabilities of Google’s Gemini API, the platform delivers a personalized, multi-faceted, and user-friendly experience. Its core feature, an AI-driven Symptom Analyzer, processes user-input health data to generate a list of probable conditions with confidence scores, impacts, and suggested home remedies. Recognizing the vital doctor–patient relationship, the system allows users to download a professional PDF report to facilitate informed discussions with healthcare providers. Additionally, the platform includes a real-time conversational AI Health Assistant, a detailed disease encyclopedia, emergency first-aid resources, and a local healthcare facility locator. Built with a modern, responsive React and Tailwind CSS frontend supporting both light and dark modes, the application exemplifies how ethical generative AI can be integrated into consumer health technology. By providing an intelligent and compassionate digital health companion, the Smart Symptom-to-Care AI fosters health literacy, reduces anxiety, and empowers users to take active roles in their wellness journey—bridging the critical gap from symptoms to professional care.

Authors

Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2025-11-09
DOI
https://doi.org/10.48175/ijarsct-29714
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Symptom-to-Care System Using AI and Machine Learning: Intelligent Health Diagnosis and Personalized Medical Guidance for Early Disease Detection

Ms. Joshi Samiksha Suresh, A. A. Khatri, Prof. S. S. Bhokare, Ms. Hinge Shrawani Navnath et al.
International Journal of Advanced Research in Science Communication and Technology
Artificial Intelligence in Healthcare and Education
article

Smart Symptom-to-Care System Using AI and Machine Learning: Intelligent Health Diagnosis and Personalized Medical Guidance for Early Disease Detection

Ms. Joshi Samiksha Suresh, A. A. Khatri, Prof. S. S. Bhokare, Ms. Hinge Shrawani Navnath, Ms. Date Pooja Hanumant
article en

Abstract

In an increasingly digital world, individuals often seek online health guidance and face overwhelming, unreliable, and complex information. To address this, Smart Symptom-to-Care AI has been developed as a comprehensive and trustworthy web application serving as the first point of contact for personal health inquiries. Leveraging the advanced reasoning and structured data capabilities of Google’s Gemini API, the platform delivers a personalized, multi-faceted, and user-friendly experience. Its core feature, an AI-driven Symptom Analyzer, processes user-input health data to generate a list of probable conditions with confidence scores, impacts, and suggested home remedies. Recognizing the vital doctor–patient relationship, the system allows users to download a professional PDF report to facilitate informed discussions with healthcare providers. Additionally, the platform includes a real-time conversational AI Health Assistant, a detailed disease encyclopedia, emergency first-aid resources, and a local healthcare facility locator. Built with a modern, responsive React and Tailwind CSS frontend supporting both light and dark modes, the application exemplifies how ethical generative AI can be integrated into consumer health technology. By providing an intelligent and compassionate digital health companion, the Smart Symptom-to-Care AI fosters health literacy, reduces anxiety, and empowers users to take active roles in their wellness journey—bridging the critical gap from symptoms to professional care.

International Journal of Advanced Research in Science Communication and Technology
Openalex Percentile: Top 74%
Artificial Intelligence in Healthcare and Education
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