18,862 resources related to Diseases
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The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE
AMC2020 is the 16th in a series of biennial international workshops on Advanced Motion Control which aims to bring together researchers from both academia and industry and to promote omnipresent motion control technologies and applications.
IEEE International Conference on Plasma Science (ICOPS) is an annual conference coordinated by the Plasma Science and Application Committee (PSAC) of the IEEE Nuclear & Plasma Sciences Society.
The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.
All areas of ionizing radiation detection - detectors, signal processing, analysis of results, PET development, PET results, medical imaging using ionizing radiation
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...
IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics. From specific algorithms to full system implementations, CG&A offers a strong combination of peer-reviewed feature articles and refereed departments, including news and product announcements. Special Applications sidebars relate research stories to commercial development. Cover stories focus on creative applications of the technology by an artist or ...
Proceedings of the 17th Southern Biomedical Engineering Conference, 1998
Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology, 2002
Summary form only given. Discovering how mechanical force can regulate the function of proteins and subsequently cell signaling is needed to reveal the molecular basis of several diseases where mechanical forces play a critical role in their onset or progression, including cardiovascular diseases and osteoporosis. We have developed nanoanalytical tools to investigate whether cells can mechanically unfold proteins, and how ...
2009 IEEE International Symposium on IT in Medicine & Education, 2009
Objective: To study the effect of IFN-alpha2b on HBVDNA and inducement to CD25 of the patients with chronic hepatitis B. Methods: All of patients were divided into two groups and treated by IFN-alpha2b, routine medicine, respectively. The levels of HBV-DNA in PBMC and serum, and CD25 and CD25 mRNA, and anti-IFN-IgG were respectively detected by real-time PCR, biotin- streptavidin (BSA) ...
2008 IEEE International Conference on Computational Cybernetics, 2008
Regression is one of the efficient tools that are used in statistics. Obviously, when we want to explain the an accuracy between statistic variables caused by fuzzy quantities instead of probable structure, we should create other tools that enable us to estimate uncertain parameters under condition of new structure. Fuzzy linear regression is a method for estimation of fuzzy parameters ...
2013 IEEE 3rd International Conference on Computational Advances in Bio and medical Sciences (ICCABS), 2013
Hepatitis C virus (HCV) is a major cause of liver disease world-wide and the leading cause of liver transplantation in developed countries. There are 7 major genotypes divided into >100 subtypes, with genotype 1 being responsible for the majority of infections in the US. Several risk factors predisposing patients to rapid progression of liver fibrosis have been identified. However, to ...
Q&A with Chris Berka: IEEE Brain Podcast, Episode 9
Ted Berger: Far Futures Panel - Technologies for Increasing Human Memory - TTM 2018
EMBC 2011-Keynote Lectures and Panel Discussion-PT I-Subra Suresh
Molecular Diagnostics for STIs - Gary Schoolnik - IEEE EMBS at NIH, 2019
Paper & Microfluidic Systems for Infectious Disease Diagnostics - Catherine Klapperich - IEEE EMBS at NIH, 2019
Honors 2020: Mark S. Humayun Wins the IEEE Medal for Innovations in Healthcare Technology
Panel: Integrating POC Testing for HLBS Diseases into Clinical Care - IEEE EMBS at NIH, 2019
Q&A with Dr. Elisa Konofagou: IEEE Brain Podcast, Episode 10
Q&A with Sri Sarma: IEEE Brain Podcast, Episode 2
Applying Control Theory to the Design of Cancer Therapy
IEEE Magnetics 2014 Distinguished Lectures - Tim St Pierre
Considerations for Adoption of POC for STI - Barbara Van Der Pol - IEEE EMBS at NIH, 2019
Implantable Wireless Medical Devices and Systems
Brave New Brain-Tech | IEEE TechEthics Panel
Summary form only given. Discovering how mechanical force can regulate the function of proteins and subsequently cell signaling is needed to reveal the molecular basis of several diseases where mechanical forces play a critical role in their onset or progression, including cardiovascular diseases and osteoporosis. We have developed nanoanalytical tools to investigate whether cells can mechanically unfold proteins, and how mechanical stretching changes their function. Fibronectin is an ideal model system to study the effect of force on function, since it mechanically couples the extracellular matrix of cells, via the transmembrane integrins, to the cytoskeleton. Fibronectin is composed of repeating modules that regulates many cellular functions, including cell adhesion, cell migration and proliferation. Fluorescence resonance energy transfer (FRET) between multiple donor and acceptor fluorophores attached to single fibronectin molecules was utilized as a tool to distinguish a range of protein conformations in cell culture, from compact to extended, to hyperextended with several functional modules being unfolded by cells stretching fibronectin fibrils. Structural predictions how mechanical forces may change the functional states of fibronectin where obtained using steered molecular dynamic simulations. Learning how cells can alter the structure and function of ECM proteins by mechanical stretching has profound implications for the design of biomaterials and in tissue engineering.
Objective: To study the effect of IFN-alpha2b on HBVDNA and inducement to CD25 of the patients with chronic hepatitis B. Methods: All of patients were divided into two groups and treated by IFN-alpha2b, routine medicine, respectively. The levels of HBV-DNA in PBMC and serum, and CD25 and CD25 mRNA, and anti-IFN-IgG were respectively detected by real-time PCR, biotin- streptavidin (BSA) and ELISA. Results: After treatment for 24 and 48 weeks, the total negative rates of HBV-DNA in PBMC, serum and HBeAg were 36.36%, 39.39%, 40.91% and 42.42%, 51.52%, 53.03%, respectively. There was significant difference between in the two groups (P < 0.05 ~ P <0.01). The level of CD25 either in silence or in inducement was low in chronic hepatitis B. Only was 4 (6.06%) cases with anti-IFN-IgG(+) and little discrepancy between in two groups (P > 0.05). Conclusions: IFN-alpha2b has better effect on HBV-DNA. CD25 can be induced by IFN-alpha2b so that the active T cells play key role against HBVDNA in hosts. Low level of anti-IFN-IgG can be produced during the treatment.
Regression is one of the efficient tools that are used in statistics. Obviously, when we want to explain the an accuracy between statistic variables caused by fuzzy quantities instead of probable structure, we should create other tools that enable us to estimate uncertain parameters under condition of new structure. Fuzzy linear regression is a method for estimation of fuzzy parameters that can be useful for estimation of relationship between variables, when the number of observations is few and the interaction of those is vague and uncertain. When speak on phrases like quality of life, intelligence quotient, etc., we will find out there is no precise and classic definition and seems that there is not any position for these concepts and tools in determining effective agents in the theorem of classic sets. A result in respect to this prospect and aim of research, we consider the effective agents on quality of life of heart diseases using fuzzy linear regression that has been developed by Tanaka.
Hepatitis C virus (HCV) is a major cause of liver disease world-wide and the leading cause of liver transplantation in developed countries. There are 7 major genotypes divided into >100 subtypes, with genotype 1 being responsible for the majority of infections in the US. Several risk factors predisposing patients to rapid progression of liver fibrosis have been identified. However, to date, there are no conclusive studies supporting the role of HCV genetic heterogeneity in progression of liver disease. Here, consensus sequences of the HCV 1b Core, NS3 and NS5b genomic regions obtained from patients with known rate of fibrosis progression (RFP), who have been identified through a study of cohorts of hepatitis C patients with (n=22) and without (n=20) liver transplantation, were analyzed. All HCV sequences were linked to RFP and transplantation status. Based on RFP all patients were classified into 2 classes with rapid (RP) and slow (SP) progression to fibrosis. A set of Bayesian networks (BN) and linear projection (LP) models was generated using nucleotide (nt) sequences and nt physicochemical properties, such as hydrophobicity, polarity, dipole moment, surface area and stacking area, to examine HCV genetic association to RFP. Both types of models consider inter- relationships among polymorphic nt sites and associate them to RFP. Clustering of HCV variants based on physicochemical properties in LP graphs as well as BN analysis of nt sequences revealed similarity among HCV variants sampled from patients of same RFP class. Especially tight clustering was observed for HCV variants from SP class in LP model. Both models allow for the identification of the most RFP-relevant genetic features of HCV. Models constructed using these features classified HCV strains into 2 RFP classes with the 85%-93% accuracy in validation assays regardless of the transplantation status, thus indicating a significant robustness of the models and suggesting a potential application of the identified genetic features as markers for detection of RFP. This is the first report of HCV genetic markers strongly associated with RFP. The apparent HCV genetic association to yearly RFP in all patients studied here has significant implications for understanding the contribution of HCV genetic diversity to RFP and offers a new framework for molecular surveillance of the HCV-related disease and viral diseases in general.
Chagas disease is a major public health problem in South American countries, in the Venezuelan case, the heart is the mainly affected organ. The parasite that produces the disease invades the myocardium, causes muscle and conduction system degeneration, leading to abnormal ventricular contractility and conduction. Late potential (LP) analysis can detect abnormal electric behavior of the ventricles, which has been correlated with the presence of ventricular tachycardia episodes. Time domain methods for LP analysis are widely used but they are affected by other cardiac pathologies, i.e., branch blocks (BE), which are found simultaneously with abnormal ventricular conduction phenomena in chagasic patients. The use of an orthogonal lead vectorspectral combination using the Hartley transform has demonstrated to be a simple frequency domain method for the interpretation of abnormal ventricular potentials. This work uses the latter approach for LP analysis of high resolution ECG (HRECG) records of chagasic patients. The vectorspectral magnitude (S) was computed as the sum of the DHT spectra components of the XYZ leads in the frequency bands of 60 to 300 Hz and -300 to -60 Hz, for each chagasic patient group and a healthy subject control group in a time window at the end of QRS. Results showed that S is significantly lower in healthy subjects (63.5/spl plusmn/23.8 /spl mu/V) than in chagasic patients with abnormal electrocardiogram (89.2/spl plusmn/43.7 /spl mu/V), p<0.05. The vector spectral analysis is a simple frequency domain method for LP study, the results showed that the method can detect positive patients with generalized myocardial disease.
Ambient air pollution has been a worldwide concern with a devastating impact on the health of populations, while increasing the burden on public health systems. Assessing the adverse health effects of air pollution is vital for forming disease control policies. This study investigates the excess risk of 6 air pollutants for 21 disease groups (observed in outpatient visits) through the Poisson regression modeling. Daily air quality data and 1.6 million outpatient visit records from Shenzhen, China are used in the study. The outpatient visits are classified into 21 disease groups according to the International Classification of Diseases, Tenth Revision. The results show that associations between air pollutants and diseases vary across different disease groups. Specifically, the following disease classes are significantly associated with air pollution: blood, metabolic, ophthalmological, circulatory, respiratory, digestive, musculoskeletal, connective tissue, and genitourinary diseases. Nitrogen dioxide, particulate matter less than 10 μm in diameter (PM10), particulate matter less than 2.5 μm in diameter (PM 2.5), and air quality index have the most extensive impact on more than ten disease groups. A health effect graph is built to support public health management decision-making and provide residents with information about health effects of air pollution.
Inhalers are devices which deliver medication to the airways in the treatment of chronic respiratory diseases. When used correctly inhalers relieve and improve patients' symptoms. However, adherence to inhaler medication has been demonstrated to be poor, leading to reduced clinical outcomes, wasted medication, and higher healthcare costs. There is a clinical need for a system that can accurately monitor inhaler adherence as currently no method exists to evaluate how patients use their inhalers between clinic visits. This paper presents a method of automatically evaluating inhaler adherence through acoustic analysis of inhaler sounds. An acoustic monitoring device was employed to record the sounds patients produce while using a Diskus dry powder inhaler, in addition to the time and date patients use the inhaler. An algorithm was designed and developed to automatically detect inhaler events from the audio signals and provide feedback regarding patient adherence. The algorithm was evaluated on 407 audio files obtained from 12 community dwelling asthmatic patients. Results of the automatic classification were compared against two expert human raters. For patient data for whom the human raters Cohen's kappa agreement score was , results indicated that the algorithm's accuracy was 83% in determining the correct inhaler technique score compared with the raters. This paper has several clinical implications as it demonstrates the feasibility of using acoustics to objectively monitor patient inhaler adherence and provide real-time personalized medical care for a chronic respiratory illness.
The Chagas¿ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the Chagas¿ disease, it is important to detect and measure the coronary damage of the patient. In this paper, we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of error-correcting output codes (ECOC) is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs.
The study of the segmentation of MRI Spine Image is of crucial importance for computer aided medical image identifying and clinical studies of neurological pathology. Computer characterization of a vertebra or disk is of limited clinical value if that structure cannot be accurately segmented and identified. However, Manual operations of tracking these structures are so tedious that automated method of spine tracking and segmentation are in high demand. In this paper, a vertebral disks segmentation method is proposed. The method can locate and label the disks through locating the spinal cord with Hough Transform. The efficiency of the proposed method is demonstrated by experiments using real MR images provided by College of Medicine, University of Cincinnati.
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Physical Sciences Platform Scientist Position in the Physical Sciences Platform (PSP) at SRI
Sunnybrook Research Institute (SRI)