Oncology/Hematology

Deep learning-based protoacoustic signal denoising for proton range verification.

Proton therapy is a type of radiation therapy that can provide better dose distribution compared to ...

Clinical approaches for integrating machine learning for patients with lymphoma: Current strategies and future perspectives.

Machine learning (ML) approaches have been applied in the diagnosis and prediction of haematological...

Predicting the survival of patients with pancreatic neuroendocrine neoplasms using deep learning: A study based on Surveillance, Epidemiology, and End Results database.

BACKGROUND: The study aims to evaluate the performance of three advanced machine learning algorithms...

A deep learning approach for automatic delineation of clinical target volume in stereotactic partial breast irradiation (S-PBI).

Accurate and efficient delineation of the clinical target volume (CTV) is of utmost significance in ...

Letter to the Editor - Update from Ukraine: Development of the Cloud-based Platform for Patient-centered Telerehabilitation of Oncology Patients with Mathematical-related Modeling.

This Letter to the Editor provides an update on the research from the Glushkov Institute of Cybernet...

Comparison of surgical completeness in patients operated on conventional open total thyroidectomy (OT) or trans-axillary robot-assisted total thyroidectomy (RATT) by a single axillary approach.

Trans-axillary robot-assisted total thyroidectomy (RATT) is nowadays worldwide accepted but the comp...

Benign vs malignant vertebral compression fractures with MRI: a comparison between automatic deep learning network and radiologist's assessment.

OBJECTIVE: To test the diagnostic performance of a deep-learning Two-Stream Compare and Contrast Net...

Robot-assisted Radical Cystectomy Versus Open Radical Cystectomy: A Systematic Review and Meta-analysis of Perioperative, Oncological, and Quality of Life Outcomes Using Randomized Controlled Trials.

CONTEXT: Differences in recovery, oncological, and quality of life (QoL) outcomes between open radic...

A trial deep learning-based model for four-class histologic classification of colonic tumor from narrow band imaging.

Narrow band imaging (NBI) has been extensively utilized as a diagnostic tool for colorectal neoplast...

A novel staging system based on deep learning for overall survival in patients with esophageal squamous cell carcinoma.

PURPOSE: We developed DeepSurv, a deep learning approach for predicting overall survival (OS) in pat...

Discrimination Between Glioblastoma and Solitary Brain Metastasis Using Conventional MRI and Diffusion-Weighted Imaging Based on a Deep Learning Algorithm.

This study aims to develop and validate a deep learning (DL) model to differentiate glioblastoma fro...

An Investigation about Modern Deep Learning Strategies for Colon Carcinoma Grading.

Developing computer-aided approaches for cancer diagnosis and grading is currently receiving an incr...

Neural network and spline-based regression for the prediction of salivary hypofunction in patients undergoing radiation therapy.

BACKGROUND: This study leverages a large retrospective cohort of head and neck cancer patients in or...

Impact of tumor contact surface area on collecting system entry in robot-assisted partial nephrectomy: a retrospective analysis.

BACKGROUND: Collecting system entry in robot-assisted partial nephrectomy may occur even in cases sh...

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories.

Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicati...

Deep learning-based methods for classification of microsatellite instability in endometrial cancer from HE-stained pathological images.

BACKGROUND: Microsatellite instability (MSI) is one of the essential tumor biomarkers for cancer tre...

Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.

OBJECTIVES: Using contrast-enhanced computed tomography (CECT) and deep learning technology to devel...

Generalising uncertainty improves accuracy and safety of deep learning analytics applied to oncology.

Uncertainty estimation is crucial for understanding the reliability of deep learning (DL) prediction...

Detection of metastasis of mediastinal lymph nodes in lung cancer patients with an artificial intelligence model.

Deep learning based synthetic CT from cone beam CT generation for abdominal paediatric radiotherapy.

. Adaptive radiotherapy workflows require images with the quality of computed tomography (CT) for re...

Deep learning for diagnosis of malign pleural effusion on computed tomography images.

BACKGROUND: The pleura is a serous membrane that surrounds the lungs. The visceral surface secretes ...