Lung Cancer

Lung cancer research intensely focuses on improving early detection and prognosis prediction to reduce mortality rates. Current efforts utilize advanced machine learning models, including convolutional neural networks, vision transformers, and large language models, to analyze multi-modal data such as CT scans, PET scans, genomic information, and patient records, often employing techniques like multi-modal fusion and attention mechanisms to enhance accuracy. These advancements aim to improve diagnostic accuracy, personalize treatment plans, and refine survival predictions, ultimately leading to better patient outcomes and informing clinical decision-making. The integration of these AI-driven approaches with traditional methods holds significant promise for transforming lung cancer care.

Papers

April 10, 2023

LCDctCNN: Lung Cancer Diagnosis of CT scan Images Using CNN Based Model
Muntasir Mamun, Md Ishtyaq Mahmud, Mahabuba Meherin, Ahmed Abdelgawad
Deep Learning State of the Art CT Image Lung Cancer Model Based Deep Learning Lung Cancer Detection

March 28, 2023

Soft-prompt tuning to predict lung cancer using primary care free-text Dutch medical notes
Auke Elfrink, Iacopo Vagliano, Ameen Abu-Hanna, Iacer Calixto
Language Model Natural Language Processing Prompt Tuning Lung Cancer Word Representation Soft Prompt Tuning Primary Health Care

March 14, 2023

EGFR mutation prediction using F18-FDG PET-CT based radiomics features in non-small cell lung cancer
Hector Henriquez, Diana Fuentes, Francisco Suarez, Patricio Gonzalez
Radiomics Feature Lung Cancer EGFR Mutation

February 5, 2023

Deep Learning Approach for Early Stage Lung Cancer Detection
Saleh Abunajm, Nelly Elsayed, Zag ElSayed, Murat Ozer
Deep Learning Model Deep Learning Approach Lung Cancer Lung Nodule Malignancy Lung Cancer Screening

December 15, 2022

Attention-based Multiple Instance Learning for Survival Prediction on Lung Cancer Tissue Microarrays
Jonas Ammeling, Lars-Henning Schmidt, Jonathan Ganz, Tanja Niedermair, Christoph Brochhausen-Delius, Christian Schulz, Katharina Breininger, Marc Aubreville
Multiple Instance Learning Survival Prediction Lung Cancer Multiple Instance Proportional Hazard

November 17, 2022

Machine Learning-Assisted Recurrence Prediction for Early-Stage Non-Small-Cell Lung Cancer Patients
Adrianna Janik, Maria Torrente, Luca Costabello, Virginia Calvo, Brian Walsh, Carlos Camps, Sameh K. Mohamed, Ana L. Ortega, Vít Nováček, Bartomeu Massutí, Pasquale Minervini, M. Rosario Garcia Campelo, Edel del Barco, Joaquim Bosch-Barrera, Ernestina Menasalvas, Mohan Timilsina, Mariano Provencio
New Machine Lung Cancer Recurrence Prediction

November 12, 2022

A Radiogenomics Pipeline for Lung Nodules Segmentation and Prediction of EGFR Mutation Status from CT Scans
Ivo Gollini Navarrete, Mohammad Yaqub
Human Prediction Computed Tomography Radiomics Feature Early Detection Lung Cancer Lung Nodule Segmentation EGFR Mutation

November 10, 2022

Perfectly predicting ICU length of stay: too good to be true
Sandeep Ramachandra, Gilles Vandewiele, David Vander Mijnsbrugge, Femke Ongenae, Sofie Van Hoecke
Random Forest Simple Classifier Lung Cancer Short Term Methodological Flaw

November 7, 2022

Multimodal Learning for Non-small Cell Lung Cancer Prognosis
Yujiao Wu, Yaxiong Wang, Xiaoshui Huang, Fan Yang, Sai Ho Ling, Steven Weidong Su
Multimodal Data Multimodal Learning Lung Cancer Survival Analysis Deep Survival Model

August 5, 2022

Deep Learning Neural Network for Lung Cancer Classification: Enhanced Optimization Function
Bhoj Raj Pandit, Abeer Alsadoon, P. W. C. Prasad, Sarmad Al Aloussi, Tarik A. Rashid, Omar Hisham Alsadoon, Oday D. Jerew
Convolutional Neural Network Deep Neural Network Image Reconstruction Lung Cancer Convolutional Filter Autoencoder Model

July 4, 2022

Efficient Lung Cancer Image Classification and Segmentation Algorithm Based on Improved Swin Transformer
Ruina Sun, Yuexin Pang
Medical Image Analysis Swin Transformer Efficient Transformer Lung Cancer Segmentation Algorithm Lung Nodule Malignancy Segmentation Target Lung Cancer Detection

May 30, 2022

Zero-Shot and Few-Shot Learning for Lung Cancer Multi-Label Classification using Vision Transformer
Fu-Ming Guo, Yingfang Fan
LeArning Abstract Vision Transformer Zero Shot Classification Code Pre Trained Vision Transformer Lung Cancer

April 26, 2022

RadioPathomics: Multimodal Learning in Non-Small Cell Lung Cancer for Adaptive Radiotherapy
Matteo Tortora, Ermanno Cordelli, Rosa Sicilia, Lorenzo Nibid, Edy Ippolito, Giuseppe Perrone, Sara Ramella, Paolo Soda
Multimodal Data Multimodal Learning Radiomics Feature Lung Cancer Multimodal Approach Adaptive Radiotherapy Multimodal Paradigm

April 24, 2022

Colorectal cancer survival prediction using deep distribution based multiple-instance learning
Xingyu Li, Jitendra Jonnagaddala, Min Cen, Hong Zhang, Xu Steven Xu
Survival Prediction Lung Cancer Colorectal Cancer Instance Learning Multiple Instance Cancer Survival

March 18, 2022

Imaging-based histological features are predictive of MET alterations in Non-Small Cell Lung Cancer
Rohan P. Joshi, Bolesław L. Osinski, Niha Beig, Lingdao Sha, Kshitij Ingale, Martin C. Stumpe
Histopathological Image Lung Cancer Cell Representation Cell Morphology MET Overexpression

March 5, 2022

Machine Learning Applications in Lung Cancer Diagnosis, Treatment and Prognosis
Yawei Li, Xin Wu, Ping Yang, Guoqian Jiang, Yuan Luo
Machine Learning Learning Based Approach Machine Learning Application Lung Cancer Prognosis Prediction Accurate Treatment

February 14, 2022

A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images
Nikita Shvetsov, Morten Grønnesby, Edvard Pedersen, Kajsa Møllersen, Lill-Tove Rasmussen Busund, Ruth Schwienbacher, Lars Ailo Bongo, Thomas K. Kilvaer
Whole Slide Image Machine Learning Approach Lung Cancer Tumor Cell Lymphocyte Detection Tumor Infiltrating Lymphocyte

January 1, 2022

Deep Learning Applications for Lung Cancer Diagnosis: A systematic review
Hesamoddin Hosseini, Reza Monsefi, Shabnam Shadroo
Deep Learning Convolutional Neural Network Systematic Review Deep Learning Algorithm Deep Learning Application Lung Cancer

December 27, 2021

Classification of Histopathology Images of Lung Cancer Using Convolutional Neural Network (CNN)
Neha Baranwal, Preethi Doravari, Renu Kachhoria
Convolutional Neural Network Classification Code Histopathological Image Histopathology Image Lung Cancer

November 17, 2021

Segmentation of Lung Tumor from CT Images using Deep Supervision
Farhanaz Farheen, Md. Salman Shamil, Nabil Ibtehaz, M. Sohel Rahman
Segmentation Based Approach CT Image Lung Cancer Deep Supervision Discrete Wavelet Transform Tumor Detection Lung Originated Tumor Segmentation

Lung Cancer

Papers

LCDctCNN: Lung Cancer Diagnosis of CT scan Images Using CNN Based Model

Soft-prompt tuning to predict lung cancer using primary care free-text Dutch medical notes

EGFR mutation prediction using F18-FDG PET-CT based radiomics features in non-small cell lung cancer

Deep Learning Approach for Early Stage Lung Cancer Detection

Attention-based Multiple Instance Learning for Survival Prediction on Lung Cancer Tissue Microarrays

Machine Learning-Assisted Recurrence Prediction for Early-Stage Non-Small-Cell Lung Cancer Patients

A Radiogenomics Pipeline for Lung Nodules Segmentation and Prediction of EGFR Mutation Status from CT Scans

Perfectly predicting ICU length of stay: too good to be true

Multimodal Learning for Non-small Cell Lung Cancer Prognosis

Deep Learning Neural Network for Lung Cancer Classification: Enhanced Optimization Function

Efficient Lung Cancer Image Classification and Segmentation Algorithm Based on Improved Swin Transformer

Zero-Shot and Few-Shot Learning for Lung Cancer Multi-Label Classification using Vision Transformer

RadioPathomics: Multimodal Learning in Non-Small Cell Lung Cancer for Adaptive Radiotherapy

Colorectal cancer survival prediction using deep distribution based multiple-instance learning

Imaging-based histological features are predictive of MET alterations in Non-Small Cell Lung Cancer

Machine Learning Applications in Lung Cancer Diagnosis, Treatment and Prognosis

A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images

Deep Learning Applications for Lung Cancer Diagnosis: A systematic review

Classification of Histopathology Images of Lung Cancer Using Convolutional Neural Network (CNN)

Segmentation of Lung Tumor from CT Images using Deep Supervision