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Abeer Aqeel

FAST · 2022 · I18-0636

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Phone

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GitHub

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Academic

Program

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CGPA

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Year

2022

Education

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Address

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DOB

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Career

Current role

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Target role

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Skills

Python, React, TensorFlow, Visual Studio

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.

Machine Learning and Imaging processing based Lung diseases detection application (MILDDA) 
 
We made an application that detects lung diseases such as COVID-19, pneumonia, lung cancer and, 
tuberculosis using chest x-rays. The radiologists can upload medical  images. The images are then processed and cleaned first, then they are passed through an optimized Visual Geometry Group (VGG) which then classifies the images into diseases. The probability of a given disease is also shown to give an accuracy measure. This system helps point out the critical cases in a particular class/disease. This system also makes the detection of Covid-19 faster. This system be there to help the doctors and radiologists as they will make the final decision for the patient. This system also detects the severity of each disease and classifies it into mild, moderate and severe. 
Features include: 
-Detection of lung disease such as lung cancer, pneumonia, tuberculosis, COVID-19. 
-Detection of the severity of each disease classified into mild, moderate and severe. 
-Upload reports, prescription and patient history. 
-View reports, prescription and patient history. 
 
 
 
 
 
 
 
 
 
Technology Used: 
Python, React, TensorfLow,   
4.6, Visual Studio 
Supervisor Name: 
Mr. Bilal Khalid Dar 
Group Members:   
Abeer Aqeel (I18 - 0636)

AI enrichment

Abeer Aqeel developed a machine learning application for detecting lung diseases like COVID-19 and pneumonia using chest X-rays and an optimized VGG model. The system processes medical images to classify diseases and their severity, providing a decision-support tool for radiologists.

Skills (AI)

["Python", "React", "TensorFlow", "Machine Learning", "Image Processing", "Computer Vision", "VGG Architecture"]

Status: ai_done

Provenance

Source file: Graduate Directory FAST School of Computing 2022 Final Version (07-06-2022).pdf
From job #25 page 238
Created: 1778170963