SymptoScan, an AI-Powered Medical Diagnosis System

SymptoScan is an AI-based system that analyzes symptoms reported by patients along with their medical histories and diagnostic test results. It employs machine learning, deep learning, and natural language processing (NLP) techniques to achieve this. By connecting with electronic health record (EHR) systems and telemedicine platforms, SymptoScan helps doctors provide accurate diagnoses and timely care, even in remote areas or places with limited resources. The system compares patient input against large clinical datasets to create probability-weighted differential diagnoses. It also provides real-time decision support during virtual consultations. Moreover, SymptoScan includes a medical imaging module for X-ray, MRIs, and CT scans. This module uses convolutional neural networks to identify possible abnormalities, thereby improving the detection accuracy. The platform aims to address common healthcare challenges, such as delays in diagnosis, misdiagnosis, and resource shortages. It also focuses on data security, algorithm fairness, and ethical standards. In summary, SymptoScan merges AI capabilities with medical expertise to create an efficient and accessible diagnostic tool for modern healthcare.

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Publication Details

Journal
International Research Journal on Advanced Engineering Hub (IRJAEH)
Published
2025-10-15
DOI
https://doi.org/10.47392/irjaeh.2025.0563
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

SymptoScan, an AI-Powered Medical Diagnosis System

C B Gaurav Ganapathy, G Karthiga, V Ajith, Burla Rajamouli
International Research Journal on Advanced Engineering Hub (IRJAEH)
Brain Tumor Detection and Classification
article

SymptoScan, an AI-Powered Medical Diagnosis System

C B Gaurav Ganapathy, G Karthiga, V Ajith, Burla Rajamouli
article en

Abstract

SymptoScan is an AI-based system that analyzes symptoms reported by patients along with their medical histories and diagnostic test results. It employs machine learning, deep learning, and natural language processing (NLP) techniques to achieve this. By connecting with electronic health record (EHR) systems and telemedicine platforms, SymptoScan helps doctors provide accurate diagnoses and timely care, even in remote areas or places with limited resources. The system compares patient input against large clinical datasets to create probability-weighted differential diagnoses. It also provides real-time decision support during virtual consultations. Moreover, SymptoScan includes a medical imaging module for X-ray, MRIs, and CT scans. This module uses convolutional neural networks to identify possible abnormalities, thereby improving the detection accuracy. The platform aims to address common healthcare challenges, such as delays in diagnosis, misdiagnosis, and resource shortages. It also focuses on data security, algorithm fairness, and ethical standards. In summary, SymptoScan merges AI capabilities with medical expertise to create an efficient and accessible diagnostic tool for modern healthcare.

International Research Journal on Advanced Engineering Hub (IRJAEH)Vol. 3(10)
Al-Ameen College of Pharmacy (IN)
Openalex Percentile: Top 64%
Brain Tumor Detection and Classification
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