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!

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

Detecting various characteristics of glioblastoma using Deep Learning

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.

A breast cancer prediction using Wisconsin-Breast Cancer (Diagnostics) dataset

Revolutionizing Kidney Cancer Detection: Harnessing AI to Predict Renal Cell Carcinoma.

Laboratory Catalog and Archive Service (LabCAS) Backend

DeepHealth Annotate is a web-based tool for viewing and annotating DICOM images. Annotation metadata can be exported in JSON format to be used for a variety of purposes, such as creating training input for deep learning models that use bounding box algorithms.

Construct and analyze CNN, NN and LogR to detect skin cancer by image

In this project I have used deep learning to build a skin cancer detection model with TensorFlow

(WIP) 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".