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Chronic Kidney Disease (CKD) is an increasingly prevalent condition affecting 13% of the US population. The disease is often a silent condition, making its diagnosis challenging. Identifying CKD stages from standard office visit records can help in early detection of the disease and lead to timely intervention. The dataset we use is highly imbalanced. We propose a hierarchical meta-classification...
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...
This paper describes an offline PC based system to classify normal and abnormal heart sound signals from heart sound audio files. The system reads the selected heart sound signal, automatically segments the heart sound signals into samples, extract the feature of each samples using cross-correlation method and classify the samples using the hierarchical multilayer perceptron network. Matlab GUI is...
Preserving privacy is becoming a key apprehension as personal data is publicly available in recent years. Most of the present Privacy Preserving Data Publishing (PPDP) methods could not process multiple, heterogeneous sensitive attributes with different levels of sensitivity requirements. This motivates us to suggest a novel methodology that can handle multiple heterogeneous (both numerical and categorical)...
In this paper we present the development of a noninvasive method for the evaluation of the degree deterioration of the diabetic foot using terahertz time domain spectroscopy. The study is based on the monitoring of hydration of the skin on the sole of the foot.
The region of interest (RoI) has the most useful information in image processing since the targeted objects are covered in this area. By determining the precise position of RoI, a computer-based identification will be able to work more efficiently, to give a better contribution in system and to eliminate objects that may intrude overall process. In malaria disease, the existence of Plasmodium can...
Differential privacy is an approach that preserves patient privacy while permitting researchers access to medical data. This paper presents mechanisms proposed to satisfy differential privacy while answering a given workload of range queries. Representing input data as a vector of counts, these methods partition the vector according to relationships between the data and the ranges of the given queries...
Automatically extracting phenotypes (i.e., the composite of ones observable characteristics/traits) from free text such as scientific literature or clinical notes and associating phenotypes with diseases is an important task. Such associations can be used in, for example, recommending candidate genes for diseases, investigating drug targets, or performing differential diagnosis. In this paper, we...
Myocardial Infarction (MI) and Arrhythmia (AR) are serious heart diseases. Human identification of these diseases from raw electrocardiography (ECG) signals is tedious and expensive. In recent studies, these diseases have been identified and localized individually using multi-channel ECG data. We explored for the robust detection of both MI and AR from ECG signal using a minimalistic (single channel)...
This work proposes multiclass deep learning classification of Alzheimer's disease (AD) using novel texture and other associated features extracted from structural MRI. Two distinct learning models (Model 1 and 2) are presented where both include subcortical area specific feature extraction, feature selection and stacked auto-encoder (SAE) deep neural network (DNN). The models learn highly complex...
Automatic identification of side branch and main vascular measurements in IVOCT images take critical roles in pre-interventional decision making for coronary artery disease treatment. Very little works have been presented on these tasks. In this paper, we proposed a novel side branch identification algorithm which utilizes a newly defined global curvature feature to identify the ostium of side branch...
Xpert MTB/RIF (Cepheid) and GenoType MTBDRplus (Hain Lifescience) are two widely used tests for rapid diagnosis of tuberculosis. The aim of this study is to compare Xpert MTB/RIF and GenoType MTBDRplus to determine overall accuracy of diagnosis using these two tests. Based on search on PubMed, Embase and Google Scholar databases, publications were identified that compared Xpert MTB/RIF and GenoType...
A wearable wireless sensing system for assisting patients affected by Parkinson’s disease is proposed. It uses integrated micro-electro-mechanical inertial sensors able to recognize the episodes of involuntary gait freezing. The system operates in real time and is designed for outdoor and indoor applications. Standard tests were performed on a noticeable number of patients and healthy persons and...
This paper presents the development of an automatic system for the classification of tooth wear disease diagnosis. Abnormal detection, disease detection and classification of oral images are substantial in the clinical research. Automatic diagnosis of the oral disease helps the medical practitioner to make decisions easily about the diagnosis process. The diagnosis models can be analyzed with the...
The cardiovascular disease is one of the most common causes of death around the world. The analysis of electrocardiograms (ECGs) is an important tool in early diagnosis of arrhythmias. However, sometime the measurement data would be corrupted by noises which may cause by the wrong equipment operation, poor contact of the electrode, or even the breath of the users. These noises would make cardiologists...
This work reports a field-deployable “sample-to-answer” molecular diagnostic system (AnyMDx) for species-specific malaria detection at the point of need. The portable nucleic acid diagnostic system uses a disposable microfluidic disc, which incorporates integrated sample preparation steps of DNA extraction, purification, elution, and amplification. Built on our previous success with highly sensitive...
The availability of Electronic Health Records (EHR) in health care settings provides terrific opportunities for early detection of patients' potential diseases. While many data mining tools have been adopted for EHR-based disease early detection, Linear Discriminant Analysis (LDA) is one of the most widely-used statistical prediction methods. To improve the performance of LDA for early detection of...
Early diagnosis of stroke is essential for timely prevention and treatment. Investigation shows that measures extracted from various risk parameters carry valuable information for the prediction of stroke. This research work investigates the various physiological parameters that are used as risk factors for the prediction of stroke. Data was collected from International Stroke Trial database and was...
Selectivity, accuracy and fast response are the challenges in current sensors; there is a huge requirement of more simplified designs. In this paper, we have designed and simulated MEMS based bio sensor for detecting Tuberculosis (TB) using FEM tool. Comparing with conventional techniques, the proposed design is more robust, reliable, price effective, very fast and highly sensitive. Two types of actuation...
Smoking tobacco products has become a deadly and prevalent habit. It is a known fact that smoking negatively affects the health, economic expenditures, and social life of not only users but also second hand smokers (people's exposure to smoke). Inhaling tobacco smoke can make people vulnerable to nicotine addiction. Correspondingly, second hand smokers may become daily or less than daily smokers in...
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