InDRI: Intelligent Diagnosis Radiology Images

The need for an early screening and Computer-Aided Diagnosis (CAD) system based on Artificial Intelligence (AI) for the field of radiology is essential to realize considering the large impact of lung diseases globally. However, developing AI requires a lot of data, which is a challenge because data in the health sector tends to be limited in quantity and has disparities between diagnostic categories (data imbalance). To overcome this issue, DINO ViT models was trained with the publicly available COVID-19 Radiography Database in our previous study. The model was subsequently implemented into a web application, with this study focusing on the development of a prototype for the application. The study found this application can be useful for medical personnel and doctors in carrying out early screening and CAD. Meanwhile, it also highlighted the general unfamiliarity with AI applications among medical staff, emphasizing the need for increased education and training on AI's role in healthcare.

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Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/icoris63540.2024.10903684
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.40
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article

InDRI: Intelligent Diagnosis Radiology Images

Gregorius Natanael Elwirehardja, Imelda Liana Ritonga, Kuncahyo Setyo Nugroho, Bens Pardamean et al.
1 citations
Radiomics and Machine Learning in Medical Imaging
0.40
article

InDRI: Intelligent Diagnosis Radiology Images

Gregorius Natanael Elwirehardja, Imelda Liana Ritonga, Kuncahyo Setyo Nugroho, Bens Pardamean, Mahmud Isnan, Roby Pahala Januario Gultom, Elida Afni Lubis
article en
1 citations

Abstract

The need for an early screening and Computer-Aided Diagnosis (CAD) system based on Artificial Intelligence (AI) for the field of radiology is essential to realize considering the large impact of lung diseases globally. However, developing AI requires a lot of data, which is a challenge because data in the health sector tends to be limited in quantity and has disparities between diagnostic categories (data imbalance). To overcome this issue, DINO ViT models was trained with the publicly available COVID-19 Radiography Database in our previous study. The model was subsequently implemented into a web application, with this study focusing on the development of a prototype for the application. The study found this application can be useful for medical personnel and doctors in carrying out early screening and CAD. Meanwhile, it also highlighted the general unfamiliarity with AI applications among medical staff, emphasizing the need for increased education and training on AI's role in healthcare.

Binus University (ID), Medan Area University (ID)
Openalex Percentile: Top 31%
Radiomics and Machine Learning in Medical Imaging
0.40
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