Oncology/Hematology

Deep Learning to Estimate RECIST in Patients with NSCLC Treated with PD-1 Blockade.

Real-world evidence (RWE), conclusions derived from analysis of patients not treated in clinical tri...

Detecting mouse squamous cell carcinoma from submicron full-field optical coherence tomography images by deep learning.

The standard medical practice for cancer diagnosis requires histopathology, which is an invasive and...

The utility of a deep learning-based algorithm for bone scintigraphy in patient with prostate cancer.

OBJECTIVE: Bone scintigraphy has often been used to evaluate bone metastases. Its functionality is e...

Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice.

BACKGROUND: Colon cancer is one of the leading causes of cancer deaths in the USA and around the wor...

Augmented Reality to Guide Selective Clamping and Tumor Dissection During Robot-assisted Partial Nephrectomy: A Preliminary Experience.

Robotic Resection of Postero-Superior Liver Segments (7,8) (with Video).

BACKGROUND: Surgical resection is the standard treatment for colorectal liver metastases. Parenchyma...

Prediction of early recurrence of hepatocellular carcinoma after resection using digital pathology images assessed by machine learning.

Hepatocellular carcinoma (HCC) is a representative primary liver cancer caused by long-term and repe...

Re: Oncological outcome according to attainment of pentafecta after robot-assisted radical cystectomy in patients with bladder cancer in the multicentre KORARC database. BJU Int 2020 July 18. DOI: 10.1111/ bju.15178.

Cancer gene expression profiles associated with clinical outcomes to chemotherapy treatments.

BACKGROUND: Machine learning (ML) methods still have limited applicability in personalized oncology ...

Brain tumor segmentation using 3D Mask R-CNN for dynamic susceptibility contrast enhanced perfusion imaging.

The segmentation of neoplasms is an important part of radiotherapy treatment planning, monitoring di...

Editorial for "MRI-Based Deep Learning Model for Distant Metastasis-Free Survival in Locoregionally Advanced Nasopharyngeal Carcinoma".

GP-GAN: Brain tumor growth prediction using stacked 3D generative adversarial networks from longitudinal MR Images.

Brain tumors are one of the major common causes of cancer-related death, worldwide. Growth predictio...

A comprehensive review of deep learning in colon cancer.

Deep learning has emerged as a leading machine learning tool in object detection and has attracted a...

Myricitrin inhibits vascular endothelial growth factor-induced angiogenesis of human umbilical vein endothelial cells and mice.

In the present study, the protective effects of myricitrin against vascular endothelial growth facto...

Simple low-cost approaches to semantic segmentation in radiation therapy planning for prostate cancer using deep learning with non-contrast planning CT images.

PURPOSE: Deep learning has shown great efficacy for semantic segmentation. However, there are diffic...

Convolutional neural networks versus radiologists in characterization of small hypoattenuating hepatic nodules on CT: a critical diagnostic challenge in staging of colorectal carcinoma.

Our objective was to compare the diagnostic performance and diagnostic confidence of convolutional n...

Liver imaging features by convolutional neural network to predict the metachronous liver metastasis in stage I-III colorectal cancer patients based on preoperative abdominal CT scan.

BACKGROUND: Introducing deep learning approach to medical images has rendered a large amount of un-d...

Deep-learning-assisted biophysical imaging cytometry at massive throughput delineates cell population heterogeneity.

The association of the intrinsic optical and biophysical properties of cells to homeostasis and path...

Extracting and classifying diagnosis dates from clinical notes: A case study.

Myeloproliferative neoplasms (MPNs) are chronic hematologic malignancies that may progress over long...

Development and Interpretation of Multiple Machine Learning Models for Predicting Postoperative Delayed Remission of Acromegaly Patients During Long-Term Follow-Up.

Some patients with acromegaly do not reach the remission standard in the short term after surgery b...

Computed tomography-based deep-learning prediction of neoadjuvant chemoradiotherapy treatment response in esophageal squamous cell carcinoma.

BACKGROUND: Deep learning is promising to predict treatment response. We aimed to evaluate and valid...