Oncology/Hematology

Introduction of robot-assisted radical hysterectomy for early stage cervical cancer: impact on complications, costs and oncologic outcome.

INTRODUCTION: The objective was to assess the impact of robot-assisted radical hysterectomy (RRH) on surgical and oncologic outcome and costs compared with open radical hysterectomy (ORH) at a tertiary referral center in Sweden.

A novel computer-aided diagnosis system for breast MRI based on feature selection and ensemble learning.

Breast cancer is a common cancer among women. With the development of modern medical science and information technology, medical imaging techniques have an increasingly important role in the early detection and diagnosis of breast cancer. In this paper, we propose an automated computer-aided diagnosis (CADx) framework for magnetic resonance imaging (MRI). The scheme consists of an ensemble of seve...

Cardiac and renal complications of carfilzomib in patients with multiple myeloma.

Clinical trials with carfilzomib have indicated a low but reproducible incidence of cardiovascular and renal toxicities. Among 60 consecutive myeloma ...

RABiT-II: Implementation of a High-Throughput Micronucleus Biodosimetry Assay on Commercial Biotech Robotic Systems.

We demonstrate the use of high-throughput biodosimetry platforms based on commercial high-throughput/high-content screening robotic systems. The cytok...

Improved image quality with simultaneously reduced radiation exposure: Knowledge-based iterative model reconstruction algorithms for coronary CT angiography in a clinical setting.

BACKGROUND: The aim of this study was to assess the potential for radiation dose reduction using knowledge-based iterative model reconstruction (K-IMR...

Identification of miRNA-mRNA Modules in Colorectal Cancer Using Rough Hypercuboid Based Supervised Clustering.

Differences in the expression profiles of miRNAs and mRNAs have been reported in colorectal cancer. Nevertheless, information on important miRNA-mRNA ...

A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers.

The treatment and management of early stage estrogen receptor positive (ER+) breast cancer is hindered by the difficulty in identifying patients who r...

Analysis of cancer-related lncRNAs using gene ontology and KEGG pathways.

BACKGROUND: Cancer is a disease that involves abnormal cell growth and can invade or metastasize to other tissues. It is known that several factors ar...

A case-based reasoning system based on weighted heterogeneous value distance metric for breast cancer diagnosis.

OBJECTIVE: We present the implementation and application of a case-based reasoning (CBR) system for breast cancer related diagnoses. By retrieving sim...

A retrospective study on screening and management of osteoporosis in breast cancer women treated with aromatase inhibitors in Libya.

Negative health effects of aromatase inhibitors (AI) treatments on bones such as osteoporosis are evidenced. This impact of the aromatase inhibitors o...

Automatic data source identification for clinical trial eligibility criteria resolution.

Clinical trial coordinators refer to both structured and unstructured sources of data when evaluating a subject for eligibility. While some eligibilit...

Performance analysis of a machine learning flagging system used to identify a group of individuals at a high risk for colorectal cancer.

Individuals with colorectal cancer (CRC) have a tendency to intestinal bleeding which may result in mild to severe iron deficiency anemia, but for man...

A machine learning classifier trained on cancer transcriptomes detects NF1 inactivation signal in glioblastoma.

BACKGROUND: We have identified molecules that exhibit synthetic lethality in cells with loss of the neurofibromin 1 (NF1) tumor suppressor gene. Howev...

Minimally Invasive Surgery: The Emerging Role in Gastric Cancer.

Minimally invasive surgical techniques are an emerging option in the staging and management of gastric cancer in the United States and elsewhere. Alth...

Gradient Boosted Decision Tree Classification of Endophthalmitis Versus Uveitis and Lymphoma from Aqueous and Vitreous IL-6 and IL-10 Levels.

PURPOSE: To investigate the effectiveness of gradient boosting to classify endophthalmitis versus uveitis and lymphoma by intraocular cytokine levels.

Use of Model Predictive Control and Artificial Neural Networks to Optimize the Ultrasonic Release of a Model Drug From Liposomes.

The use of echogenic liposomes to deliver chemotherapeutic agents for cancer treatment has gained wide recognition in the last 20 years. Cancerous cel...

Dermatologist-level classification of skin cancer with deep neural networks.

Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially ...

CyNetSVM: A Cytoscape App for Cancer Biomarker Identification Using Network Constrained Support Vector Machines.

One of the important tasks in cancer research is to identify biomarkers and build classification models for clinical outcome prediction. In this paper...

Predicting prostate tumour location from multiparametric MRI using Gaussian kernel support vector machines: a preliminary study.

The performance of a support vector machine (SVM) algorithm was investigated to predict prostate tumour location using multi-parametric MRI (mpMRI) da...

Analysis of specific serum markers of colon carcinoma using a Bhattacharyya-based support vector machine.

We aimed to evaluate the specificity of 12 tumor markers related to colon carcinoma and identify the most sensitive index. Bhattacharyya distance was ...