can Artificial Neural Networks be used to analyse Clinical Trial Data ? How ?
83542
Not so much analyze as model. In other words, the ANN can be used to "fit" your data to a mathematical model through the process of "training" the ANN with your data. This would be useful for making predictions, etc. Also, you could run analyses on the predicted outputs from the ANN model, but I do not know if this would be of value to you in your work.
1044420
The value of textual statistics is now widely acknowledged in many branches of the social sciences, reflecting the fact that there are few fields of research in which the text is not a major element for analysis.\n\nThe statistical processing may be of responses to open questions, interviews, texts and even individual itineraries. The procedures are numerous and can be adapted to different kinds of material. The aim in the present article is to give a broad overview of the various applications of these methods, ranging from the most traditional to the most recent, and focusing on both the methodology used and the results obtained.
892708
Probably a t-test. \n\nTell us what hypothesis you are testing.
581150
I hope, this can help you:\n\nLa Barre and Lowy (2001): Improvements in methods for calculating virus titer estimating TCID50 and plaque assays. J. Virol. Methods, Vol. 96, pp. 107-126.\n\nThis article is free at www.sciencedirect.com
401965
Here is a lengthy article on the ethics of using Nazi medical experimental data:\nhttp://www.jlaw.com/Articles/NaziMedEx.html
726852
It all depends on how much different you expect the results to be between the experimental group and the control group. I am on simvastatin and have gone periods drinking more green tea. Have not watched my HDL levels closely enough to compared effects. \n\nI use statcalc in EpiInfo to run sample size calculations and find that is easy and accurate. I think that would work for your experiment and your question.
14038
I think it is a very good website.\n\nhttp://www.ncrr.nih.gov/biomedical_tech.asp
829621
This any good\n\nhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9473085&dopt=Abstract
783090
u can use artificial inteligence in data mining the information on organic chemistry.\n\nAlso you can simulate, model and predict the chemical reactions using software based on artificial interlligence
1137561
http://www.pnas.org/cgi/content/full/102/19/7014
1017021
The research done with mice and spinal cord injury is fascinating, yet does not touch the neural networks involved in memory and cognition, only motor function.  Much research has gone into embryonic stem cell research which could hopefully reverse the effects that the plaques have already caused on the brain.  Even more interesting work is being done in prevention.  Like many illnesses it is easier to treat if it never happens and like many illnesses it seems that exercise can help prevent the disease.  With the aging population I believe the interest in a cure and possibly vaccines for prevention may be on the way soon.
561294
Try here:\n\nhttp://biomed.brown.edu/Courses/BI108/BI108_2004_Groups/Group04/Drug_Efficacy.htm
237683
Try:\nhttp://www.nlm.nih.gov/medlineplus/ency/article/003058.htm
223884
try www.ncbi.org/com (i forget)
411024
It can go far beyond that, as well.  If a study wasn't set up correctly, then there can BE no 'correct' interpretation.  This is especially common in drug testing.  Often companies are in such a hurry to get a new drug on the shelf that they don't take all the precautions in setting up their studies that they probably should.  For example, they don't conduct tests on as many people as they should, or they inadvertantly bias their data by not taking a random sample.  The problem usually stems from the fact that a doctor is the one responsible for running the tests, not a statistician.
509983
How you use statistical tools to analyze your data depends entirely on what kind of data you have and the questions you are trying to answer with your data.  Some kinds of data lend themselves to descriptive analysis, in which you summarize your findings with means, medians, standard deviations, etc.  Other data are suitable for formal hypothesis testing, which calls for the application of statistical tools such as t-tests, analysis of variance, linear regression, multiple regression, proportional hazards modeling, life table analysis, etc.  Ideally, the preparatory phase of a research project would include a consultation with someone familiar with biostatistics before the data are ever collected.\n\nHowever, you can make a start by going to the following website:\n\nhttp://en.wikipedia.org/wiki/Statistics\n\nYou will learn a lot in a short period of time by going there.  But be careful!  Application of statistical tools in biomedical research is not a cookbook operation.  You would be well advised to consult with someone knowledgeable, who can inspect your data and offer advice about how to analyze them.  Such a person can also help you interpret the results of any statistical testing you do.  This is not always straightforward; misinterpretation of data and their analysis will lead to failure to get your papers published, at best, or worse, the misleading of the medical community and the general public about potentially serious issues.
481901
A neural network is an interconnected group of biological neurons. In modern usage the term can also refer to artificial neural networks, which are constituted of artificial neurons. Thus the term 'Neural Network' specifies two distinct concepts:\n\n   1. A biological neural network is a plexus of connected or functionally related neurons in the peripheral nervous system or the central nervous system. In the field of neuroscience, it most often refers to a group of neurons from a nervous system that are suited for laboratory analysis.\n   2. Artificial neural networks were designed to model some properties of biological neural networks, though most of the applications are of technical nature as opposed to cognitive models.