Designing a Deep Learning Tool for Disease Detection

Abstract—Doc Plus is a medical help platform that utilizes AI for healthcare professionals with deep learning models and chatbot-based knowledge recall. The platform contains two Convolutional Neural Network (CNN)-based models for detecting Alzheimer's disease and lung cancer based on medical images like MRI and CT scans for diagnosis. The platform also consists of two AI chatbots: one that delivers information related to diseases and the other that gives prescription details in the medical field. The site is developed with Streamlit and utilizes transfer learning models such as ResNet and EfficientNet for increased accuracy. Although chatbot capabilities have been implemented effectively, the disease detection models so far suffer from overfitting, restricting real-world application. The project will help medical professionals by enhancing diagnostic effectiveness and remote disease evaluation. Future research will address model generalization to improve dependability in clinical practice. Keywords—component, formatting, style, styling, insert (key words)

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-04-24
DOI
https://doi.org/10.55041/ijsrem45680
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
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article

Designing a Deep Learning Tool for Disease Detection

Muhammed Nashath
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Artificial Intelligence in Healthcare
article

Designing a Deep Learning Tool for Disease Detection

Muhammed Nashath
article en

Abstract

Abstract—Doc Plus is a medical help platform that utilizes AI for healthcare professionals with deep learning models and chatbot-based knowledge recall. The platform contains two Convolutional Neural Network (CNN)-based models for detecting Alzheimer's disease and lung cancer based on medical images like MRI and CT scans for diagnosis. The platform also consists of two AI chatbots: one that delivers information related to diseases and the other that gives prescription details in the medical field. The site is developed with Streamlit and utilizes transfer learning models such as ResNet and EfficientNet for increased accuracy. Although chatbot capabilities have been implemented effectively, the disease detection models so far suffer from overfitting, restricting real-world application. The project will help medical professionals by enhancing diagnostic effectiveness and remote disease evaluation. Future research will address model generalization to improve dependability in clinical practice. Keywords—component, formatting, style, styling, insert (key words)

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(04)
Openalex Percentile: Top 90%
Artificial Intelligence in Healthcare
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