Pathology

Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes.

The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological source...

Prospective identification of hematopoietic lineage choice by deep learning.

Differentiation alters molecular properties of stem and progenitor cells, leading to changes in their shape and movement characteristics. We present a deep neural network that prospectively predicts lineage choice in differentiating primary hematopoietic progenitors using image patches from brightfield microscopy and cellular movement. Surprisingly, lineage choice can be detected up to three gener...

An Evolutionary Method for Financial Forecasting in Microscopic High-Speed Trading Environment.

The advancement of information technology in financial applications nowadays have led to fast market-driven events that prompt flash decision-making a...

Palpation force modulation strategies to identify hard regions in soft tissue organs.

This paper presents experimental evidence for the existence of a set of unique force modulation strategies during manual soft tissue palpation to loca...

Design and analysis of a tendon-based computed tomography-compatible robot with remote center of motion for lung biopsy.

Nowadays, biopsy is a decisive method of lung cancer diagnosis, whereas lung biopsy is time-consuming, complex and inaccurate. So a computed tomograph...

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...

An Extended SNOMED CT Concept Model for Observations in Molecular Genetics.

Molecular genetics laboratory reports are multiplying and increasingly of clinical importance in diagnosis and treatment of cancer, infectious disease...

Using a genetic-fuzzy algorithm as a computer aided diagnosis tool on Saudi Arabian breast cancer database.

The computer-aided diagnosis has become one of the major research topics in medical diagnostics. In this research paper, we focus on designing an auto...

Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection.

OBJECTIVES: Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. ...

A deep learning approach for the analysis of masses in mammograms with minimal user intervention.

We present an integrated methodology for detecting, segmenting and classifying breast masses from mammograms with minimal user intervention. This is a...

Design and preliminary evaluation of a self-steering, pneumatically driven colonoscopy robot.

Colonoscopy is a diagnostic procedure to detect pre-cancerous polyps and tumours in the colon, and is performed by inserting a long tube equipped with...

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 ...

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 ...

Three-Class Mammogram Classification Based on Descriptive CNN Features.

In this paper, a novel classification technique for large data set of mammograms using a deep learning method is proposed. The proposed model targets ...

Induction of Fas-Mediated Apoptosis by Interferon-γ is Dependent on Granulosa Cell Differentiation and Follicular Maturation in the Rat Ovary.

Fas ligand (FasL) and its receptor Fas have been implicated in granulosa cell apoptosis during follicular atresia. Although interferon-gamma (IFN-γ) i...

Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma.

BACKGROUND AND OBJECTIVE: The O-methylguanine-DNA-methyltransferase (MGMT) promoter methylation has been shown to be associated with improved outcomes...

Epicardial adipose tissue and myocardial ischemia assessed by computed tomography perfusion imaging and invasive fractional flow reserve.

BACKGROUND: Epicardial adipose tissue (EAT) is a metabolically active fat depot that is associated with incident coronary artery disease (CAD) and maj...

A Novel Microspheres Formulation of Puerarin: Pharmacokinetics Study and In Vivo Pharmacodynamics Evaluations.

The aim of this study was to investigate the pharmacokinetics and pharmacodynamics of puerarin loaded carboxymethyl chitosan microspheres (Pue-CCMs). ...

Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software with subsequent machine learning: Detection of apoptosis in renal tissue.

OBJECTIVE: The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA f...