Oncology/Hematology

Deep learning model to predict Epstein-Barr virus associated gastric cancer in histology.

The detection of Epstein-Barr virus (EBV) in gastric cancer patients is crucial for clinical decision making, as it is related with specific treatment responses and prognoses. Despite its importance, the limited medical resources preclude universal EBV testing. Herein, we propose a deep learning-based EBV prediction method from H&E-stained whole-slide images (WSI). Our model was developed using 31...

The Impact of Artificial Intelligence on Health Equity in Oncology: Scoping Review.

BACKGROUND: The field of oncology is at the forefront of advances in artificial intelligence (AI) in health care, providing an opportunity to examine the early integration of these technologies in clinical research and patient care. Hope that AI will revolutionize health care delivery and improve clinical outcomes has been accompanied by concerns about the impact of these technologies on health eq...

Revealing low-temperature plasma efficacy through a dose-rate assessment by DNA damage detection combined with machine learning models.

Low-temperature plasmas have quickly emerged as alternative and unconventional types of radiation that offer great promise for various clinical modali...

Comparison of single-port and multi-port Retzius-sparing robot-assisted laparoscopic prostatectomy.

Dissemination of robotic surgical technology for robot-assisted laparoscopic prostatectomy (RALP) has yielded advancements including the Retzius-spari...

Emergence of MXene and MXene-Polymer Hybrid Membranes as Future- Environmental Remediation Strategies.

The continuous deterioration of the environment due to extensive industrialization and urbanization has raised the requirement to devise high-performa...

Automated detection of patterned single-cells within hydrogel using deep learning.

Single-cell analysis has been widely used in various biomedical engineering applications, ranging from cancer diagnostics, and immune response monitor...

Positive surgical margin's impact on short-term oncological prognosis after robot-assisted partial nephrectomy (MARGINS study: UroCCR no 96).

The oncological impact of positive surgical margins (PSM) after robot-assisted partial nephrectomy (RAPN) is still under debate. We compared PSM and N...

SkiNet: A deep learning framework for skin lesion diagnosis with uncertainty estimation and explainability.

Skin cancer is considered to be the most common human malignancy. Around 5 million new cases of skin cancer are recorded in the United States annually...

Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-Net.

The identification and quantification of liver lesions changes in longitudinal contrast enhanced CT (CECT) scans is required to evaluate disease statu...

Long-term comparative outcome analysis of a robot-assisted laparoscopic prostatectomy with retropubic radical prostatectomy by a single surgeon.

We aimed to report a comprehensive outcome analysis of robot-assisted laparoscopic prostatectomies (RALP) performed by a single surgeon and compared i...

Three-dimensional simulation of the pancreatic parenchyma, pancreatic duct and vascular arrangement in pancreatic surgery using a deep learning algorithm.

Three-dimensional surgical simulation, already in use for hepatic surgery, can be used in pancreatic surgery. However, some problems still need to be ...

Prediction of chemotherapy-related complications in pediatric oncology patients: artificial intelligence and machine learning implementations.

Although the overall incidence of pediatric oncological diseases tends to increase over the years, it is among the rare diseases of the pediatric popu...

Oral epithelial cell segmentation from fluorescent multichannel cytology images using deep learning.

BACKGROUND AND OBJECTIVES: Cytology is a proven, minimally-invasive cancer screening and surveillance strategy. Given the high incidence of oral cance...

3Ddose verification in prostate proton therapy with deep learning-based proton-acoustic imaging.

Dose delivery uncertainty is a major concern in proton therapy, adversely affecting the treatment precision and outcome. Recently, a promising techniq...

An Unsupervised Deep Learning-Based Model Using Multiomics Data to Predict Prognosis of Patients with Stomach Adenocarcinoma.

METHODS: Patients (363 in total) with stomach adenocarcinoma from The Cancer Genome Atlas (TCGA) cohort were included. An autoencoder was constructed ...

A nomogram to predict pathologic T2 stage in candidates to robot-assisted radical prostatectomy with iT3 prostate cancer on preoperative multiparametric MRI: results from a multi-institutional collaboration.

In candidates to robot-assisted radical prostatectomy (RARP) for locally advanced (iT3) prostate cancer on preoperative MRI, the performance of MRI fo...

Fast Deformable Image Registration for Real-Time Target Tracking During Radiation Therapy Using Cine MRI and Deep Learning.

PURPOSE: We developed a deep learning (DL) model for fast deformable image registration using 2-dimensional sagittal cine magnetic resonance imaging (...

Magnetic torque-driven living microrobots for increased tumor infiltration.

Biohybrid bacteria-based microrobots are increasingly recognized as promising externally controllable vehicles for targeted cancer therapy. Magnetic f...

Predicting Chemical Carcinogens Using a Hybrid Neural Network Deep Learning Method.

Determining environmental chemical carcinogenicity is urgently needed as humans are increasingly exposed to these chemicals. In this study, we develop...

Deep Learning Hybrid Techniques for Brain Tumor Segmentation.

Medical images play an important role in medical diagnosis and treatment. Oncologists analyze images to determine the different characteristics of dea...