Monkeypox Disease Detection using Deep Learning | Python IEEE Machine Learning Final Year Project

Monkeypox Disease Detection using Deep Learning | Python IEEE Machine Learning Final Year Project 2023 - 2024.
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📌IEEE Base Paper Title: Monkeypox Diagnosis with Interpretable Deep Learning.
🔬Our Proposed Project Title: Monkey pox Disease Detection using Deep Learning.
💡Implementation Code: PYTHON.
🔬Algorithm / Model Used: ResNet50V2 Architecture.
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.5000/.

IEEE Base paper Abstract:
As the world gradually recovers from the impacts of COVID-19, the recent global spread of Monkeypox disease has raised concerns about another potential pandemic, highlighting the urgency of early detection and intervention to curb its transmission. Deep Learning (DL) based disease prediction presents a promising solution, offering affordable and accessible diagnostic services. In this study, we harnessed Transfer Learning (TL) techniques to tweak and assess the performance of an array of six different DL models, encompassing VGG16, InceptionResNetV2, ResNet50, ResNet101, MobileNetV2, VGG19, and Vision Transformer (ViT). Among this diverse collection, it was the modified versions of the VGG19 and MobileNetV2 models that outshone the others, boasting striking accuracy rates ranging from an impressive 93% to an astounding 99%. Our results echo the findings of recent research endeavours that similarly showcased enhanced performance when developing disease diagnostic models armed with the power of TL. To add to this, we made use of Local Interpretable Model Agnostic Explanations (LIME) to lend a sense of transparency to our model’s predictions, and to identify the crucial features correlating with the onset of Monkeypox disease. These findings offer significant implications for disease prevention and control efforts, particularly in remote and resource-limited areas.

REFERENCE:
MD MANJURUL AHSAN, MD SHAHIN ALI, MD. MEHEDI HASSAN, TAREQUE ABU ABDULLAH, KISHOR DATTA GUPTA, ULAS BAGCI, CHETNA KAUSHAL, NAGLAA F. SOLIMAN, “Monkeypox Diagnosis with Interpretable Deep Learning”, IEEE Access ( Early Access ), 2023.

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