Integrative analysis has been primarily used to prioritize disease genes or chromosomal regions for experimental testing, to discover disease subtypes or to predict patient survival or other clinical variables. The ultimate goal of this work is to propose a machine learning approach which is functional in both data fusion and supervised learning. We further analyzed the potential benefits of merging microarray and clinical data sets for prognostic application in breast cancer diagnosis.
We integrate microarray and clinical data into one mathematical model, for the development of highly homogeneous classifiers in clinical decision support. For this purpose, we present a kernel based integration framework in which each data set is transformed
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To verify the merit of the proposed approach over the single data sources such as clinical and microarray data, the LS-SVM were built on all data sets individually for classifying cancer patients. Next, GEVD and kernel GEVD were used as pre-processing step. Then the data in the projected space (scores) have used to build the LS-SVM classifier. Results shows that these types of integration information helped us to achieve better prediction performances than considering single data sets. Integration of different data sources are relevant in cancer studies for better diagnosis, prognosis and personnel therapy.
In addition, the results suggest that kernel based data integration increases the predictive performance of clinical decision support models. This indicates that there might be non-linear pattern in the data that effectively modelled with kernel based techniques. Finally weighted LS-SVM approach was used for the integration of both microarray and clinical kernel functions and performed subsequent classifications. The weighted LS-SVM classifier proposes a new optimization framework to solve the problem of classification using features
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Such studies are required to determine, which data sets are most significant to be considered as weighting matrix. The proposed weighted LS-SVM classifier integrates heterogeneous data sets to achieve good performing and affordable classifiers. The results suggest that the use of our integration approach on gene expression and clinical data can improve the performance of decision making in cancer.
We proposed a weighted LS-SVM classifier for the integration of two data sources and further prediction task. Each data set is represented with a kernel matrix, based on the RBF kernel function. The proposed clinical classifier gives a step towards improving predictions for individual patients about prognosis, metastatic phenotype and therapy responses.
Because the parameters (bandwidth for kernel matrices and regularization term of weighted LS-SVM) had to be optimized, all possible combinations of these parameters were investigated with a LOO-CV. Since these parameters optimization strategy is time consuming, one can further investigate a parameter optimization criterion for kernel GEVD and weighted LS-SVM.
The applications of proposed method are not limited to clinical and
After, the color space transformation we are going to extracts the texture vector from that image using sparse texture model. The texture vectors are represented as a set of distributions which is used to cluster the texture data using K-means clustering algorithm. Finding the number of clusters which consists set of texture distributions used to calculate TD metric. After, calculating the TD metric, the image is over segmented using SRM algorithm, which results the image being divided into large number of regions. Next, each region is independently classified as representing normal skin or lesion based on the textural contents of that region.
The integumentary system- This system is overlaying the outer body. • Anatomical location- The integumentary system is superior or external to the body. The organs that make up this system are the skin, glands, nails, hair, and sense receptors.
The NIMS provides assistance to each state, which allows them to be prepared for any possible emergency. The five components of NIMS provided a guideline that is used throughout an emergency whether it be Federal departments, State, tribal, and local organizations. Establish a system and being able to provide possible issues that may arise and analyzed the challenges. The national integration center (NIC) ensures that the NIMS is operating at optimal level, that all training, resources, and communicating system are being meet; the NIC provides an assessment NIMS and ensures that each component is filing it responsibility. NIMS is an ideal system that was developed to respond universally to emergencies and the check and balances installed into
Computer-based algorithms provide patient-specific assistance. An early warning system that provides timely alerts designed to ensure that appropriate actions are initiated as soon as problems begin to develop. Four key applications have been developed to achieve these goals.
Today, there are endless arguments about the existing of the American dream. In “They say, I say” by Gerald Graff, Cathy Birkenstein and Russel Durst. There are four article that I have evaluated. The upside of income inequality – Gary S. Becker and Kevin M. Murphy, American Dream: dead, alive, or on hold – Brandon King, Bring on more immigrant entrepreneur – Shayan Zadeh, America remains the world’s beacon of success – Tim Roemer
Article-Nutrition and Exercise among Patient with Bipolar Among the many mental illnesses individuals suffer from, bipolar disorder (BPD) is one of the most disabling mood disorders. It is chronic condition that is linked with a substantial personal and societal cost along with general medical comorbidities, including dyslipidemia, hypertension, diabetes, obesity and cardiovascular disease (Kilbourne, Rofey, McCarthy, Post, Welsh, & Blow, 2007). It is commonly known that these medical conditions often lead to life altering challenges and most often premature deaths. However, most of these medical diagnoses can be preventable or at least manageable with a proactive lifestyle that includes a healthy diet, daily exercise and medication.
OIC is a unique and progressive center dedicated to providing evidence-based treatments and therapies to Omaha and surrounding communities. We provide integrative primary care & family medicine, mental health services, therapeutic yoga, nutrition services, acupuncture, body work and therapeutic massage, and mind – body medicine practices. Our number-one priority is creating a healing, therapeutic environment for our clients and providing the highest level of patient care and customer service. Practitioners at OIC collaborate internally across disciplines as well as with other health care professionals and practitioners in the community.
Today, money has made many people believe that you need to have a lot of money to live a great, happy life. People in the world, especially the people who don’t have as much money as the ones that do, look up to people like popular idols, because they have money. People think they have a great living life with all the money they have earned during their lives. In the short story “Why You Reckon?” by Langston Hughes, the author uses diction, colloquialism and dialect to express the fact that just because people have the money to go out to eat somewhere expensive or buy the newest clothes, does not mean that a person is happy all the time and expresses how people in the town talks. Money is what makes the world goes round and everyone has come
We must filter and customize that downloaded data for the health conditions that we primarily try to improve. Once data is customized and filtered properly, it gives us “care gaps”. Those care gaps can be easily closed out by accessing patient’s EMR or by referral. This updated data then gets uploaded back to the healthcare insurance company data set for reporting purpose. Data analytics helps health profession close the care gaps and improv care coordination between
Lastly, the lab results were evaluated using the Support Vector Machine for classification and the small-scale in-the-wild
The main objectives of dissertation that are to be analyzed and can be implemented as follows: 1. The aim of recommendation system is to provide correct recommendations to user. The ‘Mean Absolute Error’ represents the effectiveness of results. The objective of work is to reduce MAE in comparison to traditional K-Nearest Neighbor algorithm. 2.
Accept or reject innovations In the article Accepting or rejecting innovation written by Jared Diamond, he states the reasons about people accepting or rejecting innovations. The first reason is “relative economic advantage compared with existing technology” which means people will accept the innovations when they think they could make money and save money at the same time. The second reason is “social value and prestige, which can override economic benefit” which means social value could influences whether people will accept the innovations. The last reason is “compatibility with vested interest” which means people will accept or reject the innovations depends on their interests.
In the world we live in today, everyone has an opinion on what’s going on, rather it’s a news reporter, magazine blog, social media or maybe it’s just journalists. Everything argues upon “they say” versus what “I say”, which is extremely significant because everyone’s opinion is effective to someone. Likewise, in the two articles, “Watching TV Makes You Smarter” and “Thinking Outside of the Idiot Box”, both the authors created arguments on whether television makes you “smarter”, or not. In the article, “Watching TV Makes You Smarter”, the author, Steve Johnson, argues that television is significant to the brain.
Cut-off date 27 February. Part1: Essay. ‘Evaluate the contribution of a qualitative approach to research on friendship’. Part2: DE100 project report – Method.
In quantitative research, variables are identified and defined, and then relevant data is collected from study participants. A strength of this type of research is that the data is in numeric form, making it easier to interpret. It also studies the relationship between independent and dependent variables and can address questions such as does a relationship between variables exist, what is the direction of the relationship, how strong is the relationship between the variables, and what is the nature of the relationship. To be able to discover and answer the cause-and-effect relationship is a strength of quantitative research. Lastly, in quantitative research, the study can either be experimental or nonexperimental, meaning clinical trial or observational study, allowing for different types of research studies to be conducted.