Oncology/Hematology

Optical tissue clearing and machine learning can precisely characterize extravasation and blood vessel architecture in brain tumors.

Precise methods for quantifying drug accumulation in brain tissue are currently very limited, challe...

Augmented intelligence to predict 30-day mortality in patients with cancer.

An augmented intelligence tool to predict short-term mortality risk among patients with cancer coul...

Molecular insights on ABL kinase activation using tree-based machine learning models and molecular docking.

Abelson kinase (c-Abl) is a non-receptor tyrosine kinase involved in several biological processes es...

Deep Collocative Learning for Immunofixation Electrophoresis Image Analysis.

Immunofixation Electrophoresis (IFE) analysis is of great importance to the diagnosis of Multiple My...

The structure-based cancer-related single amino acid variation prediction.

Single amino acid variation (SAV) is an amino acid substitution of the protein sequence that can pot...

Multi-institutional development and external validation of machine learning-based models to predict relapse risk of pancreatic ductal adenocarcinoma after radical resection.

BACKGROUND: Surgical resection is the only potentially curative treatment for pancreatic ductal aden...

Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved.

OBJECTIVE: Evaluate the completeness of reporting of prognostic prediction models developed using ma...

Long-term cancer survival prediction using multimodal deep learning.

The age of precision medicine demands powerful computational techniques to handle high-dimensional p...

The Immune Subtypes and Landscape of Gastric Cancer and to Predict Based on the Whole-Slide Images Using Deep Learning.

BACKGROUND: Gastric cancer (GC) is a highly heterogeneous tumor with different responses to immunoth...

Unsupervised water scene dehazing network using multiple scattering model.

In water scenes, where hazy images are subject to multiple scattering and where ideal data sets are ...

Orthogonal quantification of soluble inducible T-cell costimulator (ICOS) in healthy and diseased human serum.

Inducible T-cell costimulator (ICOS), a homodimeric protein expressed on the surface of activated T-...

Artificial Intelligence in Cancer Care: Legal and Regulatory Dimensions.

Considering that artificial intelligence (AI) technologies have the potential to change cancer care,...

Clinical decision support algorithm based on machine learning to assess the clinical response to anti-programmed death-1 therapy in patients with non-small-cell lung cancer.

OBJECTIVE: Anti-programmed death (PD)-1 therapy confers sustainable clinical benefits for patients w...

A Commentary on "Long-term oncological outcomes in robotic versus laparoscopic approach for rectal cancer: A systematic review and meta-analysis" [Int. J. Surg. 80 (2020) 225-230].

Construction and Validation of a Lung Cancer Diagnostic Model Based on 6-Gene Methylation Frequency in Blood, Clinical Features, and Serum Tumor Markers.

Lung cancer has a high mortality rate. Promoting early diagnosis and screening of lung cancer is the...

Risk prediction for delayed clearance of high-dose methotrexate in pediatric hematological malignancies by machine learning.

This study aimed to establish a predictive model to identify children with hematologic malignancy at...

Artificial intelligence in tumor subregion analysis based on medical imaging: A review.

Medical imaging is widely used in the diagnosis and treatment of cancer, and artificial intelligence...

Artificial intelligence in medical imaging: implications for patient radiation safety.

Artificial intelligence, including deep learning, is currently revolutionising the field of medical ...

Deep learning for semi-automated unidirectional measurement of lung tumor size in CT.

BACKGROUND: Performing Response Evaluation Criteria in Solid Tumor (RECISTS) measurement is a non-tr...

A hierarchical deep reinforcement learning framework for intelligent automatic treatment planning of prostate cancer intensity modulated radiation therapy.

We have previously proposed an intelligent automatic treatment planning (IATP) framework that builds...

Technical Note: Dose prediction for head and neck radiotherapy using a three-dimensional dense dilated U-net architecture.

PURPOSE: Radiation therapy treatment planning is a time-consuming and iterative manual process. Cons...