Oncology/Hematology

Computational models in inflammatory bowel disease.

Inflammatory bowel disease (IBD) is a chronic and relapsing disease with multiple underlying influences and notable heterogeneity among its clinical and response-to-treatment phenotypes. There is no cure for IBD, and none of the currently available therapies have demonstrated clinical efficacies beyond 40%-60%. Data collected about its omics, pathogenesis, and treatment strategies have grown expon...

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

BACKGROUND: Artificial intelligence (AI) shows great potential to streamline the treatment planning process. However, its clinical adoption is slow due to the limited number of clinical evaluation studies and because often, the translation of the predicted dose distribution to a deliverable plan is lacking. This study evaluates two different, deliverable AI plans in terms of their clinical accepta...

A novel bone registration method using impression molding and structured-light 3D scanning technology.

Accurate bone registration is critical for computer navigation and robotic surgery. Existing registration systems are expensive, cumbersome, limited i...

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 NSCLCs harbor an activating mutation in the epide...

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 provided by a radiologist. Prostate MRI structured rep...

Multifaceted Engineered Biomimetic Nanorobots Toward Cancer Management.

The noteworthy beneficiary to date in nanotechnology is cancer management. Nanorobots are developed as the result of advancements in the nanostructure...

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 significantly different in terms of surgical complexity, requ...

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 diseases is a growing trend in recent years. In t...

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 a suitable treatment plan but is often challengin...

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 binding of a phosphate group with amino acid resid...

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 rely on the expression quantification of small gene...

Effective Cancer Subtype and Stage Prediction via Dropfeature-DNNs.

Precise cancer subtype and/or stage prediction is instrumental for cancer diagnosis, treatment and management. However, most of the existing methods b...

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 genomic stability. Here, we aimed to develop a TSG-...

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 inconsistent radiological response assessment. Promising vol...

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) that appears to be a universal cancer marker and...

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 patients' response to treatment are varied. This v...

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 progression (LTP) after tumor ablation for hepatoce...

Deep learning-based AI model for signet-ring cell carcinoma diagnosis and chemotherapy response prediction in gastric cancer.

PURPOSE: We aimed to develop a noninvasive artificial intelligence (AI) model to diagnose signet-ring cell carcinoma (SRCC) of gastric cancer (GC) and...

Machine Learning of Single Cell Transcriptomic Data From anti-PD-1 Responders and Non-responders Reveals Distinct Resistance Mechanisms in Skin Cancers and PDAC.

Immune checkpoint therapies such as PD-1 blockade have vastly improved the treatment of numerous cancers, including basal cell carcinoma (BCC). Howeve...

Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer.

BACKGROUND: The evaluation of automatic segmentation algorithms is commonly performed using geometric metrics. An analysis based on dosimetric paramet...