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Genome-wide association study (GWAS), as one primary approach for genetic studies, has been successfully applied to a variety of complex diseases, leading to the discovery of substantial disease-associated loci. These discovered associations provide unprecedented opportunities for deepening our understanding of complex diseases, such as disease-associated risk variants, genes, and pathways. However,...
Gene (microRNA) identification is a key step in understanding the cellular mechanisms. Compared with biological experiments, computational prediction of disease genes is cheaper and more effortless. In this study, we analyzed the properties of tumor-associated microRNA in mouse and found that tumor-associated genes display 8distinguishingfeatures when compared with genes not yet known to be involved...
Diabetes is one of the most prevalent diseases worldwide, and hundreds of millions of patients are suffering from diabetes and its serious complications. Early detection and early treatment are urgent needed for clinical diagnosis of diabetics. In this work, we establish a gene coexpression network framework to identify biomarkers of transcripts with highly different gene coexpression patterns in...
There are many species of tomato diseases and pests, and the pathology of which is complex. It is difficult and error-prone to simply rely on manual identification. For the ten most common tomato diseases and pests in China, This paper explores the detection algorithms on leaf images and constructs the convolution neural network model to detect tomato pests and diseases based on VGG16[8] and transfer...
Leukemia is a worldwide disease. In this paper we demonstrate that it is possible to build an automated, efficient and rapid leukemia diagnosis system. We demonstrate that it is possible to improve the precision of current techniques from the literature using the description power of well-known Convolutional Neural Networks (CNNs). We extract features from a blood smear image using pre-trained CNNs...
The current focus of our research is to detect and classify the plant disease in agricultural domain, by implementing image processing techniques. We aim to propose an innovative set of statistical texture features for classification of plant diseases images of leaves. The input images are taken by various mobile cameras. The Scale-invariant feature transform (SIFT) features used as texture feature...
Protecting plantation forests from pests and diseases are essential for keeping trees healthy and productive. Diagnosis of diseases is critical for disease management in plantation forests. For forest plantation with large concession areas, manual identification is time consuming and subjective due to inconsistency of investigator's decision. This paper proposes a method for automatic acacia leaf...
The heart disease describes a range of conditions affecting our heart. It can include blood vessel diseases such as coronary artery disease, heart rhythm problems or and heart defects. This term is often used for cardiovascular disease, i.e. narrowed or blocked blood vessels leading to a heart attack, chest pain or stroke. In our work, we analysed three available data sets: Heart Disease Database,...
Brain injuries seem to be one of the most widespread diseases. Hence, the main goal of our research was to investigate feature importance in the severe brain damages dataset according to the Glasgow Outcome Scale. This scale is recognized as one of several measures used to evaluate patients' functional ability as well as their conditions after applying brain damage therapy. The current approach is...
Glaucoma is a group of eye disorders that damage the optic nerve. Considering a single eye condition for the diagnosis of glaucoma has failed to detect all glaucoma cases accurately. A reliable computer-aided diagnosis system is proposed based on a novel combination of hybrid structural and textural features. The system improves the decision-making process after analysing a variety of glaucoma conditions...
Tuberculosis (TB) is a major health threat in the developing countries. Many patients die every year due to lack of treatment and error in diagnosis. Developing a computer-aided diagnosis (CAD) system for TB detection can help in early diagnosis and containing the disease. Most of the current CAD systems use handcrafted features, however, lately there is a shift towards deep-learning-based automatic...
Every organism emits energy around it which comprises UV-radiation, EM-radiation, infrared and thermal radiation. This energy around human body represents health condition of the subject under study. These energy fields are called as aura of the body under consideration. Several types of equipments are there to capture such energy. Kirlian camera captures the distribution of energy radiation around...
A diagnosis of a stadium of Plasmodium can help physicians in managing patients with malaria. The stadium of Plasmodium is divided into three stadiums, namely trophozoite, schizont, and gametocyte. Staging is based on the morphological characteristics of each stadium, including shape, size, texture, and color. We selected 15 features using a correlation-based feature selection method with a “best...
Diabetic Macular Edema (DME) is a common eye disease that causes irreversible vision loss for diabetic patients, if left untreated. Thus, early diagnosis of DME could help in early treatment and prevent blindness. This paper aims to create a framework based on deep learning for DME recognition on Spectral Domain Optical Coherence Tomography (SD-OCT) images through transfer learning. First, images...
Attention deficit hyperactivity disorder creates conditions for the child as s/he cannot sit calm and still, control his/her behavior and focus his/her attention on a particular issue. Five out of every hundred children are affected by the disease. Boys are three times more than girls at risk for this complication. The disorder often begins before age seven, and parents may not realize their children...
Chronic kidney disease (CKD) is a disease caused by degeneration function of the kidneys. CKD is top ten leading causes of death in the world. There are two leading causes of CKD, i.e. diabetes and hypertension. When the symptoms become more severe, the disease can only be treated with dialysis and kidney transplantation. This disease can be treated if the diagnose is conducted appropriately and quickly...
Heart disease classification is one of the most important topics in clinical decision support systems (CDSS). However, the performance of classification is greatly affected by feature selection. Canonical correlation analysis (CCA) is a popular method to extract effective features from two relevant data sets. In this paper, we employ discriminant minimum class locality preserving canonical correlation...
With the development of machine learning techniques, artificial intelligence applications in medicine are becoming hot topic in health information systems. In this research, we construct a new basic heart failure disease database which contains 1715 patients and 400 features. Then, we propose a new machine learning method called Polynomial Smooth Support Vector Machine(PSSVM) to help doctors diagnose...
In the tropical and the subtropical countries, malaria has been a challenge, which really needs a quick and precise diagnosis to put a stop or control the disease. The conventional microscopy method has some shortcomings which includes time consumption and reproducibility. Many of the alternative methods are expensive and it's not readily accessible to the developing countries that need them. In this...
Detecting diseases associated SNPs is the central goal of genetics and molecular biology. However, highthroughput techniques often provide long lists of disease SNPs candidates, and the identification of disease SNPs among the candidates set remains timeconsuming and expensive. In addition, contrasting to the number of SNPs involved, the available datasets (samples) generally have fairly small sample...
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