Other Cancers

Robot-assisted ultrasound navigation platform for 3D HIFU treatment planning: Initial evaluation for conformal interstitial ablation.

Interstitial Ultrasound-guided High Intensity Focused Ultrasound (USgHIFU) therapy has the potential...

Synergistic drug combinations and machine learning for drug repurposing in chordoma.

Chordoma is a devastating rare cancer that affects one in a million people. With a mean-survival of ...

Soft Tissue Sarcoma: Preoperative MRI-Based Radiomics and Machine Learning May Be Accurate Predictors of Histopathologic Grade.

The purpose of this study was to assess the value of radiomics features for differentiating soft ti...

The Development of a Skin Cancer Classification System for Pigmented Skin Lesions Using Deep Learning.

Recent studies have demonstrated the usefulness of convolutional neural networks (CNNs) to classify ...

Re-establishing the Role of Robot-assisted Radical Cystectomy After the 2020 EAU Muscle-invasive and Metastatic Bladder Cancer Guideline Panel Recommendations.

The EAU guidelines panel on muscle-invasive and metastatic bladder cancer (MIBC) recently recommende...

Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis.

We use deep transfer learning to quantify histopathological patterns across 17,355 hematoxylin and e...

A Deep Learning-Based Tumor Classifier Directly Using MS Raw Data.

Since the launch of Chinese Human Proteome Project (CNHPP) and Clinical Proteomic Tumor Analysis Con...

Preoperative prediction for pathological grade of hepatocellular carcinoma via machine learning-based radiomics.

OBJECTIVE: To investigate the efficacy of contrast-enhanced computed tomography (CECT)-based radiomi...

Development and Validation of a Deep-learning Model to Assist With Renal Cell Carcinoma Histopathologic Interpretation.

OBJECTIVE: To develop and test the ability of a convolutional neural network (CNN) to accurately ide...

The Impact of Artificial Intelligence in the Endoscopic Assessment of Premalignant and Malignant Esophageal Lesions: Present and Future.

In the gastroenterology field, the impact of artificial intelligence was investigated for the purpos...

Automated diagnosis of bone metastasis based on multi-view bone scans using attention-augmented deep neural networks.

Bone scintigraphy is accepted as an effective diagnostic tool for whole-body examination of bone met...

Radiomics and Artificial Intelligence for Renal Mass Characterization.

Radiomics allows for high throughput extraction of quantitative data from images. This is an area of...

A fully automated artificial intelligence method for non-invasive, imaging-based identification of genetic alterations in glioblastomas.

Glioblastoma is the most common malignant brain parenchymal tumor yet remains challenging to treat. ...

An Intelligent Diagnosis Method of Brain MRI Tumor Segmentation Using Deep Convolutional Neural Network and SVM Algorithm.

Among the currently proposed brain segmentation methods, brain tumor segmentation methods based on t...

Use of artificial intelligence in diagnosis of head and neck precancerous and cancerous lesions: A systematic review.

This systematic review analyses and describes the application and diagnostic accuracy of Artificial ...

Radiomics can predict tumour response in patients treated with Nivolumab for a metastatic renal cell carcinoma: an artificial intelligence concept.

Improving the accuracy of gastrointestinal neuroendocrine tumor grading with deep learning.

The Ki-67 index is an established prognostic factor in gastrointestinal neuroendocrine tumors (GI-NE...

A deep learning MR-based radiomic nomogram may predict survival for nasopharyngeal carcinoma patients with stage T3N1M0.

PURPOSE: To estimate the prognostic value of deep learning (DL) magnetic resonance (MR)-based radiom...

Accuracy and efficiency of an artificial intelligence tool when counting breast mitoses.

BACKGROUND: The mitotic count in breast carcinoma is an important prognostic marker. Unfortunately s...

Radiomics in liver diseases: Current progress and future opportunities.

Liver diseases, a wide spectrum of pathologies from inflammation to neoplasm, have become an increas...

Development of a Deep Learning Model to Identify Lymph Node Metastasis on Magnetic Resonance Imaging in Patients With Cervical Cancer.

IMPORTANCE: Accurate identification of lymph node metastasis preoperatively and noninvasively in pat...