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Deep learning based Diagnosis of diseases using Image Classification
Proc. Conflu.: Int. Conf. Cloud Comput., Data Sci. Eng. ; : 399-404, 2021.
Article in English | Scopus | ID: covidwho-1186094
ABSTRACT
Any disease whether it is curable or not, it must be diagnosed properly with some time in hand to take the appropriate actions in time. As it is popularly said that early detection of any disease is half cured. For detection of the diseases like Pneumonia, Covid-19, Brain Tumor Radiography, Computed Tomography are a technique popularly used nowadays. The motivation towards the study of the topic was that due to our country’s population density, the vulnerability of getting infected and not being treated nicely was exposed during the outbreak of Covid-19. The ratio of doctors in India is nearly 11456 which means 1 doctor has approximately 1456 patients to deal with. That also results in a lot of time being wasted on diagnosis, scheduling appointments, collection of reports, etc. which could prove to be critical for a patient. To reduce all the time being wasted, with the help of machine learning we intend to learn if we can predict if the patient is infected with a certain disease or not. How do we do that is by using deep learning models and analyze on the basis of a few X-Ray scan of the Chest to detect Pneumonia. © 2021 IEEE

Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Diagnostic study / Prognostic study / Screening study Language: English Journal: Proc. Conflu.: Int. Conf. Cloud Comput., Data Sci. Eng. Year: 2021 Document Type: Article

Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Diagnostic study / Prognostic study / Screening study Language: English Journal: Proc. Conflu.: Int. Conf. Cloud Comput., Data Sci. Eng. Year: 2021 Document Type: Article