My research poster presentations

LesNet (Lesion Net) is an open-source project for AI-based skin lesion detection. It aims to create a reliable tool and foster community involvement in critical AI problems. Contributions are welcome!

A comprehensive classification tool based on pure transcriptomics for precision medicine

Detecting various characteristics of glioblastoma using Deep Learning

Nuclei segmentation and classification (Cancer cells)

Prototype for skin cancer detection app in Java, with Flask backend

Lightweight neural network for binary classification of cancer metastasis in bone scan images using PyTorch. Code repository for the study entitled "A Lightweight Convolutional Neural Network for Detection of Osseous Metastasis using Feature Fusion and Attention Strategies". Presented at CVIPPR 2024.

Convolutional neural network capable of identifying skin lesions (based on the skin lesion image data set HAM10000).

Utilizing deep learning for accurate skin cancer prediction from lesion images for early diagnosis.

Kaggle Histopathologic Cancer Detection Competition

This project aims for early detection of melanoma, a type of skin cancer, using Convolutional Neural Networks (CNN).

Official repository of "Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models"

Pymaceuticals Data Analysis and Visualization

Brain tumor detection using Deep learning in MRI images

Submission Dicoding Belajar Penerapan Machine Learning untuk Android

Identification of cancer-causing variants

Predicting thyroid cancer.