Oncology/Hematology

Editorial for: "Primary Central Nervous System Lymphoma: Clinical Evaluation of Automated Segmentation on Multiparametric MRI Using Deep Learning".

A machine learning framework to trace tumor tissue-of-origin of 13 types of cancer based on DNA somatic mutation.

Carcinoma of unknown primary (CUP), defined as metastatic cancers with unknown cancer origin, occurs in 3-5 per 100 cancer patients in the United States. Heterogeneity and metastasis of cancer brings great difficulties to the follow-up diagnosis and treatment for CUP. To find the tissue-of-origin (TOO) of the CUP, multiple methods have been raised. However, the accuracies for computed tomography (...

Radiomics and "radi-…omics" in cancer immunotherapy: a guide for clinicians.

In recent years the concept of precision medicine has become a popular topic particularly in medical oncology. Besides the identification of new molec...

Automatic Detection Method for Cancer Cell Nucleus Image Based on Deep-Learning Analysis and Color Layer Signature Analysis Algorithm.

Exploring strategies to treat cancer has always been an aim of medical researchers. One of the available strategies is to use targeted therapy drugs t...

Identifying sarcopenia in advanced non-small cell lung cancer patients using skeletal muscle CT radiomics and machine learning.

BACKGROUND: Sarcopenia has been confirmed as a poor prognostic indicator of lung cancer. However, the lack of abdominal computed tomography (CT) hinde...

Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.

Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. Predicting the overall survival of breast and ovar...

Assessment of Magnetic Liposomal Paclitaxel Nanoparticles as a Potential Carrier for the Treatment of Ovarian Cancer.

This study aimed to evaluate the role of magnetic liposome nanoparticles (ML NPs) as a carrier for paclitaxel (PTX) for the treatment of ovarian canc...

Breast Cancer Histopathology Image Classification Using an Ensemble of Deep Learning Models.

Breast cancer is one of the major public health issues and is considered a leading cause of cancer-related deaths among women worldwide. Its early dia...

Breast cancer detection from biopsy images using nucleus guided transfer learning and belief based fusion.

BACKGROUND AND OBJECTIVE: Breast cancer is a frequently diagnosed cancer in women, contributing to significant mortality rates. Death rates are relati...

Classifying Breast Cancer Subtypes Using Deep Neural Networks Based on Multi-Omics Data.

With the high prevalence of breast cancer, it is urgent to find out the intrinsic difference between various subtypes, so as to infer the underlying m...

A knowledge-based intensity-modulated radiation therapy treatment planning technique for locally advanced nasopharyngeal carcinoma radiotherapy.

BACKGROUND: To investigate the feasibility of a knowledge-based automated intensity-modulated radiation therapy (IMRT) planning technique for locally ...

Endoscopic activity, tissue factor and Crohn's disease: findings in clinical remission patients.

BACKGROUND: As Crohn's disease (CD) is associated with a high risk of thromboembolic events (TE), including patients with subclinical inflammation, we...

Deep learning for risk prediction in patients with nasopharyngeal carcinoma using multi-parametric MRIs.

BACKGROUND: Magnetic resonance images (MRI) is the main diagnostic tool for risk stratification and treatment decision in nasopharyngeal carcinoma (NP...

Multimodality Imaging and Artificial Intelligence for Tumor Characterization: Current Status and Future Perspective.

Research in medical imaging has yet to do to achieve precision oncology. Over the past 30 years, only the simplest imaging biomarkers (RECIST, SUV,…) ...

Using deep learning to predict beam-tunable Pareto optimal dose distribution for intensity-modulated radiation therapy.

PURPOSE: Many researchers have developed deep learning models for predicting clinical dose distributions and Pareto optimal dose distributions. Models...

Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges.

Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of pathological changes. Cancerous cells are abnormal areas often...

Artificial Intelligence and Mechanistic Modeling for Clinical Decision Making in Oncology.

The amount of "big" data generated in clinical oncology, whether from molecular, imaging, pharmacological, or biological origin, brings novel challeng...

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 to deliver ablative treatments which conform to t...

Utilizing Artificial Intelligence for Head and Neck Cancer Outcomes Prediction From Imaging.

Artificial intelligence (AI)-based models have become a growing area of interest in predictive medicine and have the potential to aid physician decisi...

Artificial Intelligence in Lung Cancer: Bridging the Gap Between Computational Power and Clinical Decision-Making.

Lung cancer remains the most common cause of cancer death worldwide. Recent advances in lung cancer screening, radiotherapy, surgical techniques, and ...