Oncology/Hematology

A computational method for drug sensitivity prediction of cancer cell lines based on various molecular information.

Determining sensitive drugs for a patient is one of the most critical problems in precision medicine...

ChrNet: A re-trainable chromosome-based 1D convolutional neural network for predicting immune cell types.

Cells from our immune system detect and kill pathogens to protect our body against various diseases....

Histopathological characteristics and artificial intelligence for predicting tumor mutational burden-high colorectal cancer.

BACKGROUND: Tumor mutational burden-high (TMB-H), which is detected with gene panel testing, is a pr...

Chinese guideline for the application of rectal cancer staging recognition systems based on artificial intelligence platforms (2021 edition).

Superselective Ischemia in Robotic Partial Nephrectomy Does Not Provide Better Long-term Renal Function than Renal Artery Clamping in a Randomized Controlled Trial (EMERALD): Should We Take the Risk?

BACKGROUND: Superselective clamping of tumor-targeted arteries aims to eliminate ischemia of the rem...

Extraperitoneal versus transperitoneal approach for robot-assisted radical prostatectomy: a contemporary systematic review and meta-analysis.

We aim to evaluate the differences in peri-operative characteristics, surgical complications, and on...

Feasibility of deep learning-based fully automated classification of microsatellite instability in tissue slides of colorectal cancer.

High levels of microsatellite instability (MSI-H) occurs in about 15% of sporadic colorectal cancer ...

Independent real-world application of a clinical-grade automated prostate cancer detection system.

Artificial intelligence (AI)-based systems applied to histopathology whole-slide images have the pot...

Artificial Intelligence in Bulk and Single-Cell RNA-Sequencing Data to Foster Precision Oncology.

Artificial intelligence, or the discipline of developing computational algorithms able to perform ta...

Increasing prediction accuracy of pathogenic staging by sample augmentation with a GAN.

Accurate prediction of cancer stage is important in that it enables more appropriate treatment for p...

Artificial intelligence in oncology: From bench to clinic.

In the past few years, Artificial Intelligence (AI) techniques have been applied to almost every fac...

Multi-magnification-based machine learning as an ancillary tool for the pathologic assessment of shaved margins for breast carcinoma lumpectomy specimens.

The surgical margin status of breast lumpectomy specimens for invasive carcinoma and ductal carcinom...

Overcoming the limitations of patch-based learning to detect cancer in whole slide images.

Whole slide images (WSIs) pose unique challenges when training deep learning models. They are very l...

Development and initial validation of a deep learning algorithm to quantify histological features in colorectal carcinoma including tumour budding/poorly differentiated clusters.

AIMS: To develop and validate a deep learning algorithm to quantify a broad spectrum of histological...

A deep learning approach for 2D ultrasound and 3D CT/MR image registration in liver tumor ablation.

BACKGROUND AND OBJECTIVE: Liver tumor ablation is often guided by ultrasound (US). Due to poor image...

Challenges and opportunities for artificial intelligence in oncological imaging.

Imaging plays a key role in oncology, including the diagnosis and detection of cancer, determining c...

A primer on applying AI synergistically with domain expertise to oncology.

BACKGROUND: The concurrent growth of large-scale oncology data alongside the computational methods w...

Liver tumor segmentation using 2.5D UV-Net with multi-scale convolution.

Liver tumor segmentation networks are generally based on U-shaped encoder-decoder network with 2D or...

Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble.

Ensemble learning combines multiple learners to perform combinatorial learning, which has advantages...

Cytoreductive radical prostatectomy after chemohormonal therapy in patients with primary metastatic prostate cancer.

OBJECTIVE: Cytoreductive radical prostatectomy (cRP) has been proposed as local treatment option in ...

Machine-Learning-Based Evaluation of Intratumoral Heterogeneity and Tumor-Stroma Interface for Clinical Guidance.

Assessment of intratumoral heterogeneity and tumor-host interaction within the tumor microenvironmen...