Oncology/Hematology

Impact of noise reduction on radiation dose reduction potential of virtual monochromatic spectral images: Comparison of phantom images with conventional 120 kVp images using deep learning image reconstruction and hybrid iterative reconstruction.

PURPOSE: To assess the effects of deep learning image reconstruction (DLIR) and hybrid iterative rec...

Computational models in inflammatory bowel disease.

Inflammatory bowel disease (IBD) is a chronic and relapsing disease with multiple underlying influen...

Clinical evaluation of two AI models for automated breast cancer plan generation.

BACKGROUND: Artificial intelligence (AI) shows great potential to streamline the treatment planning ...

Quality in MR reporting of the prostate – improving acquisition, the role of AI and future perspectives.

The high quality of MRI reporting of the prostate is the most critical component of the service prov...

Predicting EGFR mutation status by a deep learning approach in patients with non-small cell lung cancer brain metastases.

PURPOSE: Non-small cell lung cancer (NSCLC) tends to metastasize to the brain. Between 10 and 60% of...

Multifaceted Engineered Biomimetic Nanorobots Toward Cancer Management.

The noteworthy beneficiary to date in nanotechnology is cancer management. Nanorobots are developed ...

Establishment and External Validation of a Hypoxia-Derived Gene Signature for Robustly Predicting Prognosis and Therapeutic Responses in Glioblastoma Multiforme.

OBJECTIVE: Hypoxia presents a salient feature investigated in most solid tumors that holds key roles...

Off-clamp robot-assisted partial nephrectomy for purely hilar tumors: Technique, perioperative, oncologic and functional outcomes from a single center series.

OBJECTIVES: Purely hilar lesions and those abutting the main renal artery or vein may be significant...

Quantitative features to assist in the diagnostic assessment of chronic lymphocytic leukemia progression.

The use of artificial intelligence methods in the image-based diagnostic assessment of hematological...

A Transfer-Learning-Based Deep Convolutional Neural Network for Predicting Leukemia-Related Phosphorylation Sites from Protein Primary Sequences.

As one of the most important post-translational modifications (PTMs), phosphorylation refers to the ...

Classification of subtypes including LCNEC in lung cancer biopsy slides using convolutional neural network from scratch.

Identifying the lung carcinoma subtype in small biopsy specimens is an important part of determining...

Effective Cancer Subtype and Stage Prediction via Dropfeature-DNNs.

Precise cancer subtype and/or stage prediction is instrumental for cancer diagnosis, treatment and m...

Investigating Deep Learning Based Breast Cancer Subtyping Using Pan-Cancer and Multi-Omic Data.

Breast Cancer comprises multiple subtypes implicated in prognosis. Existing stratification methods r...

GuiltyTargets: Prioritization of Novel Therapeutic Targets With Network Representation Learning.

The majority of clinical trials fail due to low efficacy of investigated drugs, often resulting from...

A Tumor Suppressor Gene-Based Prognostic Classifier Predicts Prognosis, Tumor Immune Infiltration, and Small Molecule Compounds in Breast Cancer.

Tumor suppressor genes (TSGs) play critical roles in the cell cycle checkpoints and in modulating g...

Fully automated volumetric measurement of malignant pleural mesothelioma by deep learning AI: validation and comparison with modified RECIST response criteria.

BACKGROUND: In malignant pleural mesothelioma (MPM), complex tumour morphology results in inconsiste...

G-protein coupled receptor-associated sorting protein 1 (GASP-1), a ubiquitous tumor marker, promotes proliferation and invasion of triple negative breast cancer.

We have identified the novel protein GASP-1 (G protein coupled receptor-associated sorting protein 1...

Arterial enhancing local tumor progression detection on CT images using convolutional neural network after hepatocellular carcinoma ablation: a preliminary study.

To evaluate the performance of a deep convolutional neural network (DCNN) in detecting local tumor p...

Dynamic Bayesian networks for prediction of health status and treatment effect in patients with chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) is the most common blood cancer in adults. The course of CLL and ...

Identifying Prognostic Markers From Clinical, Radiomics, and Deep Learning Imaging Features for Gastric Cancer Survival Prediction.

BACKGROUND: Gastric cancer is one of the leading causes of cancer death in the world. Improving gast...

Machine learning for tumor growth inhibition: Interpretable predictive models for transparency and reproducibility.