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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM54148

Review Paper on Disease Prediction and Doctor Connection AI System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM54148

Volume:

9 |

11 |

Nov 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM54148

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

VN

Vaishnavi Nagare1

RD

Rohit Datir2

Sk

Shivraj katkar3

BO

Bhagawat O.V.4

MK

Mahale K.I.5

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Abstract

Most people only visit a doctor when symptoms get bad enough to force a trip—fever over 102, cough that won’t stop, or pain that keeps them up. By then half the day is gone on travel and waiting, plus ₹200–300 for something that could have been caught earlier. Online searches give too many scary answers, and existing apps either predict or book doctors but never do both in one cheap, fast flow. The proposed system lets patients enter 5–10 symptoms on a simple web form and get an instant disease name with confidence score (85%+ for common cases) plus 2–3 safe home remedies. If they want a doctor, they pick from a filtered list, pay ₹50 via Razorpay, and land in a direct messaging chat with a pre-filled note: disease, confidence, symptoms. Doctors log in to see only paid requests and reply when free. Everything runs on Flask with PSQL or MYSQL storage, a scikit-learn model loaded at startup, and Razorpay for orders and verification. No extra apps, no video calls—just browser to chat in under two minutes. The setup cuts clinic load for routine cases, gives doctors micro-income, and works on any phone with Indian payments.

KEYWORDS

Symptom-Based Prediction Micro-Consultation Razorpay Integration Confidence Scoring MongoDB Storage

Cite This Article

Vaishnavi Nagare1, Rohit Datir2, Shivraj katkar3, Bhagawat O.V.4, Mahale K.I.5, "Review Paper on Disease Prediction and Doctor Connection AI System," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 11, Nov 2025. https://doi.org/10.55041/IJSREM54148

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Publication Date

11/19/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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