Oncology/Hematology

DRMDA: deep representations-based miRNA-disease association prediction.

Recently, microRNAs (miRNAs) are confirmed to be important molecules within many crucial biological processes and therefore related to various complex human diseases. However, previous methods of predicting miRNA-disease associations have their own deficiencies. Under this circumstance, we developed a prediction method called deep representations-based miRNA-disease association (DRMDA) prediction....

Integrating multiple fitting regression and Bayes decision for cancer diagnosis with transcriptomic data from tumor-educated blood platelets.

The application of machine learning in cancer diagnostics has shown great promise and is of importance in clinic settings. Here we consider applying machine learning methods to transcriptomic data derived from tumor-educated platelets (TEPs) from individuals with different types of cancer. We aim to define a reliability measure for diagnostic purposes to increase the potential for facilitating per...

Finding disagreement pathway signatures and constructing an ensemble model for cancer classification.

Cancer classification based on molecular level is a relatively routine research procedure with advances in high-throughput molecular profiling techniq...

The pervasive crisis of diminishing radiation therapy access for vulnerable populations in the United States, part 2: American Indian patients.

INTRODUCTION: American Indian/Alaska Native (AI/AN) patients with cancer disproportionally present with more advanced stages of disease and have the w...

A state-independent network of depressive, negative and positive symptoms in male patients with schizophrenia spectrum disorders.

Depressive symptoms occur frequently in patients with schizophrenia. Several factor analytical studies investigated the associations between positive,...

Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis.

Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no cheap, simple and widely available screening metho...

Brain tumor segmentation using holistically nested neural networks in MRI images.

PURPOSE: Gliomas are rapidly progressive, neurologically devastating, largely fatal brain tumors. Magnetic resonance imaging (MRI) is a widely used te...

Bladder Cancer Treatment Response Assessment in CT using Radiomics with Deep-Learning.

Cross-sectional X-ray imaging has become the standard for staging most solid organ malignancies. However, for some malignancies such as urinary bladde...

Reinforcement learning-based control of drug dosing for cancer chemotherapy treatment.

The increasing threat of cancer to human life and the improvement in survival rate of this disease due to effective treatment has promoted research in...

Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems.

Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy source...

Robotic technology in interventional cardiology: Current status and future perspectives.

Robotic technology has been utilized in cardiovascular medicine for over a decade, and over that period, its use has been expanded to percutaneous cor...

Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images.

Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect t...

An Unusual Case of Metastatic Functional Thyroid Carcinoma With a Remarkable Treatment Response to Radioactive Iodine.

Functional thyroid carcinoma is an unusual cause of thyrotoxicosis. We describe the clinical presentation and treatment of a patient with thyrotoxicos...

Network-based machine learning and graph theory algorithms for precision oncology.

Network-based analytics plays an increasingly important role in precision oncology. Growing evidence in recent studies suggests that cancer can be bet...

Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks.

Breast lesion detection using ultrasound imaging is considered an important step of computer-aided diagnosis systems. Over the past decade, researcher...

A machine learning approach to estimation of downward solar radiation from satellite-derived data products: An application over a semi-arid ecosystem in the U.S.

Shortwave solar radiation is an important component of the surface energy balance and provides the principal source of energy for terrestrial ecosyste...

An Evaluation of Artificial Neural Networks in Predicting Pancreatic Cancer Survival.

OBJECTIVE: This study aims to evaluate the development of an artificial neural network (ANN) method for predicting the survival likelihood of pancreat...

Machine Learning-Assisted Network Inference Approach to Identify a New Class of Genes that Coordinate the Functionality of Cancer Networks.

Emerging evidence indicates the existence of a new class of cancer genes that act as "signal linkers" coordinating oncogenic signals between mutated a...

TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR). To exploit this untappe...

Effects of Oleo Gum Resin of L. on Senescence in Human Dermal Fibroblasts: - Asafoetida reverses senescence in fibroblasts.

OBJECTIVES: Based on data from Chinese and Indian traditional herbal medicines, gum resin of (sometimes referred to asafetida or asafoetida) has seve...