Descriptive and Statistical Analysis on the Cancer Patients dataset

Machine learning for non small cell lung cancer nodal staging from PETCT molecular imaging

Tool for the annotation of PET-CT images in 3D Slicer. Based on MONAILabel. Paper: Multimodal Interactive Lung Lesion Segmentation: A Framework for Annotating PET/CT Images based on Physiological and Anatomical Cues

Companion for the 2023 manuscript in Cancer Epidemiology, Biomarkers & Prevention entitled "Geographic Patterns in U.S. Lung Cancer Mortality and Cigarette Smoking"

Mutation Detection in Lung Cancer Cell Lines using CNNs

Identification of Lung Cancer in Smoker Person Using Ensemble Methods Based on Gene Expression Data. Presented in IC2IE and published to IEEE.

An automated lung cancer detection project.

This repository contains a Jupyter Notebook for the analysis of Non-Small Cell Lung Cancer (NSCLC) data using various machine learning techniques.

R package for lung-cancer risk-prediction model PLCOm2012

Exploratory Data Analysis of Lung Cancer Risk Factors

Lung Preneoplasia Progression via Pathomics

Correlation Between IBSI Morphological Features and Manually-Annotated Shape Attributes on Lung Lesions at CT (MIUA 2022)

Developed a fine-tuned EfficientNetB0 model which is a pre-trained Convolutional Neural Network (CNN) model to train using lungs and colon cancer dataset and classify if the unseen image belonged to benign, adenocarcinoma or squamous cell carcinoma cancer type.

Lung Cancer Prediction Model: Leverage the power of deep learning with this TensorFlow-based project. Trained on a dataset of lung X-Ray images, the model accurately predicts cancer cases. Easily integrate and utilize the model for early detection. #HealthTech #MachineLearning

Genomic Data Commons Query