Integrating Speculation Detection and Deep Learning to Extract Lung Cancer Diagnosis from Clinical Notes

Automatic Lung Cancer Detection and Diagnosis Using Hand Crafted and Deep Learning Features

This paper presents a lung nodule detection and classification system which utilizes a combination of hand crafted and deep learning features. Hand crafted features were obtained from modified methods of bag of frequencies, and taxonomic indices. We included a robust radius estimation algorithm that resulted in an average error of 1.29 pixels. Hand crafted features were obtained from 3D low dos...

Lung nodule detection by using Deep Learning

Lung cancer is one of the most common types of cancer worldwide. It is also one of the deadliest types of cancer. However, research indicates that early detection of lung cancer significantly improves chances of survival. Using computed tomography scans of the human lungs, radiologists can detect dangerous nodules in early stages. When more people adopting for these scans, the workload on the r...

Melanoma detection with a deep learning model

Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions.    Methods: In this analytic s...

Lung nodule detection by using Deep Learning

Lung cancer is one of the most common types of cancer worldwide. It is also one of the deadliest types of cancer. However, research indicates that early detection of lung cancer significantly improves chances of survival. Using computed tomography scans of the human lungs, radiologists can detect dangerous nodules in early stages. When more people adopting for these scans, the workload on the r...

Integrating Deep Learning and Multiple Instance Learning