Oncology/Hematology

Towards the Establishment of a Biomedical Ontology for the Primary Sjögren's Syndrome.

Primary Sjögren's Syndrome (pSS) has been characterized as a hypersensitivity reaction type II systemic autoimmune chronic disease causing exocrine gland dysfunction mainly affecting women near the menopausal age. pSS patients exhibit dryness of the main mucosal surfaces and are highly prone to lymphoma development. This paper presents a first biomedical ontology for pSS based on a reference model...

Cancer Type Prediction and Classification Based on RNA-sequencing Data.

Pan-cancer analysis is a significant research topic in the past few years. Due to many advancing sequencing technologies, researchers possess more resources and knowledge to identify the key factors that could trigger cancer. Furthermore, since The Cancer Genome Atlas (TCGA) project launched, using machine learning (ML) techniques to analyze TCGA data has been recognized as a useful solution in th...

Deep Learning and Multi-Sensor Fusion for Glioma Classification Using Multistream 2D Convolutional Networks.

This paper addresses issues of brain tumor, glioma, grading from multi-sensor images. Different types of scanners (or sensors) like enhanced T1-MRI, T...

Automatic Delineation of the Clinical Target Volume in Rectal Cancer for Radiation Therapy using Three-dimensional Fully Convolutional Neural Networks.

Accurate, robust, and fast delineation of the clinical target volume (CTV) for the use in radiotherapy of rectal cancer (RC) is highly sought-after. C...

A Fully Convolutional Deep Neural Network for Lung Tumor Boundary Tracking in MRI.

Delineation of lung tumor from adjacent tissue from a series of magnetic resonance images (MRI) poses many difficulties due to the image similarities ...

Feature specific quantile normalization enables cross-platform classification of molecular subtypes using gene expression data.

MOTIVATION: Molecular subtypes of cancers and autoimmune disease, defined by transcriptomic profiling, have provided insight into disease pathogenesis...

Robotic right middle lobectomy with a subxiphoid utility port.

We present the case of a 74-year-old man with Stage IIa pulmonary adenocarcinoma, for which he underwent a robotic right middle lobectomy. A 4-armed, ...

Feasibility study of stain-free classification of cell apoptosis based on diffraction imaging flow cytometry and supervised machine learning techniques.

This study was to explore the feasibility of prediction and classification of cells in different stages of apoptosis with a stain-free method based on...

Implementation and evaluation of a sterile compounding robot in a satellite oncology pharmacy.

PURPOSE: The purpose of this study was to quantify the impact of robotic technology on efficiency, accuracy, and cost in a satellite oncology pharmacy...

3-D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2-D Trained Network.

Low-dose computed tomography (LDCT) has attracted major attention in the medical imaging field, since CT-associated X-ray radiation carries health ris...

Arash: A social robot buddy to support children with cancer in a hospital environment.

This article presents the thorough design procedure, specifications, and performance of a mobile social robot friend Arash for educational and therape...

Automated classification of multiphoton microscopy images of ovarian tissue using deep learning.

Histopathological image analysis of stained tissue slides is routinely used in tumor detection and classification. However, diagnosis requires a highl...

Predicting Corticosteroid-Free Biologic Remission with Vedolizumab in Crohn's Disease.

BACKGROUND AND AIMS: Vedolizumab (VDZ) is effective for Crohn's disease (CD) but costly and is slow to produce remission. Early knowledge of whether v...

Measuring Processes of Care in Palliative Surgery: A Novel Approach Using Natural Language Processing.

: Palliative surgical procedures are often performed for patients with limited survival. Quality measures for processes of care at the end of life are...

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide...

Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas.

Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome ...

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images.

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this...

Data-Adaptive Estimation for Double-Robust Methods in Population-Based Cancer Epidemiology: Risk Differences for Lung Cancer Mortality by Emergency Presentation.

In this paper, we propose a structural framework for population-based cancer epidemiology and evaluate the performance of double-robust estimators for...

Integrating Natural Language Processing and Machine Learning Algorithms to Categorize Oncologic Response in Radiology Reports.

A significant volume of medical data remains unstructured. Natural language processing (NLP) and machine learning (ML) techniques have shown to succes...

Neopepsee: accurate genome-level prediction of neoantigens by harnessing sequence and amino acid immunogenicity information.

BACKGROUND: Tumor-specific mutations form novel immunogenic peptides called neoantigens. Neoantigens can be used as a biomarker predicting patient res...