Other Cancers

Deep Learning Hybrid Method to Automatically Diagnose Periodontal Bone Loss and Stage Periodontitis.

We developed an automatic method for staging periodontitis on dental panoramic radiographs using the...

Radiomics and deep learning in lung cancer.

Lung malignancies have been extensively characterized through radiomics and deep learning. By provid...

Knowledge Graph-Enabled Cancer Data Analytics.

Cancer registries collect unstructured and structured cancer data for surveillance purposes which pr...

A Diagnostic Algorithm using Multi-parametric MRI to Differentiate Benign from Malignant Myometrial Tumors: Machine-Learning Method.

This study aimed to develop a diagnostic algorithm for preoperative differentiating uterine sarcoma ...

Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial.

BACKGROUND & AIMS: One-fourth of colorectal neoplasias are missed during screening colonoscopies; th...

Re: Geraldine Pignot, Antoine Thiery-Vuillemin, Jochen Walz, et al. Nephrectomy After Complete Response to Immune Checkpoint Inhibitors for Metastatic Renal Cell Carcinoma: A New Surgical Challenge? Eur Urol. In press. https://doi.org/10.1016/j.eururo.2019.12.018: The Next Surgical Frontier in Kidney Cancer: Nephrectomy After Immune Checkpoint Inhibition.

Convolutional Neural Network Can Recognize Drug Resistance of Single Cancer Cells.

It is known that single or isolated tumor cells enter cancer patients' circulatory systems. These ci...

Computer-Aided Pathologic Diagnosis of Nasopharyngeal Carcinoma Based on Deep Learning.

The pathologic diagnosis of nasopharyngeal carcinoma (NPC) by different pathologists is often ineffi...

Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy.

In this paper, we present a new Deep Convolutional Neural Networks (CNNs) dedicated to fully automat...

Convolutional Neural Networks in Predicting Nodal and Distant Metastatic Potential of Newly Diagnosed Non-Small Cell Lung Cancer on FDG PET Images.

The purpose of this study was to assess, by analyzing features of the primary tumor with F-FDG PET,...

Comparison of CBCT based synthetic CT methods suitable for proton dose calculations in adaptive proton therapy.

In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed...

High quality proton portal imaging using deep learning for proton radiation therapy: a phantom study.

Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting...

A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma.

OBJECTIVES: The evaluation of lymph node (LN) status by radiologists based on preoperative computed ...

Preoperative assessment of lymph node metastasis in Colon Cancer patients using machine learning: a pilot study.

BACKGROUND: Preoperative detection of lymph node (LN) metastasis is critical for planning treatments...

Gait-Based Machine Learning for Classifying Patients with Different Types of Mild Cognitive Impairment.

Mild cognitive impairment (MCI) may be caused by Alzheimer's disease, Parkinson's disease (PD), cere...

A machine learning-based real-time tumor tracking system for fluoroscopic gating of lung radiotherapy.

To improve respiratory-gated radiotherapy accuracy, we developed a machine learning approach for mar...

iTTCA-Hybrid: Improved and robust identification of tumor T cell antigens by utilizing hybrid feature representation.

In spite of the repertoire of existing cancer therapies, the ongoing recurrence and new cases of can...

Brain tumor segmentation and grading of lower-grade glioma using deep learning in MRI images.

Gliomas are the most common malignant brain tumors with different grades that highly determine the r...

Perioperative margin detection in basal cell carcinoma using a deep learning framework: a feasibility study.

PURPOSE: Basal cell carcinoma (BCC) is the most commonly diagnosed cancer and the number of diagnosi...

Deep convolutional neural networks for automated segmentation of brain metastases trained on clinical data.

INTRODUCTION: Deep learning-based algorithms have demonstrated enormous performance in segmentation ...

Combination Strategies for Immune-Checkpoint Blockade and Response Prediction by Artificial Intelligence.

The therapeutic concept of unleashing a pre-existing immune response against the tumor by the applic...