Collision tumour involving a rectal gastrointestinal stromal tumour with invasion of the prostate and a prostatic adenocarcinoma

Background: Gastrointestinal stromal tumours (GISTs) are the most common primary mesenchymal neoplasia in the gastrointestinal tract, although they represent only a small fraction of total gastrointestinal malignancies in adults (<2%). GISTs can be located at any level of the gastrointestinal tract; the stomach is the most common location (60-70%), in contrast to the rectum, which is most rare (4%). When a GIST invades into the adjacent prostate tissue, it can simulate prostate cancer. In this study, we report on a case comprising the unexpected collision between a rectal GIST tumour and a prostatic adenocarcinoma. Findings: We describe the complexity of the clinical, endoscopic and radiological diagnosis, of the differential diagnosis based on tumour biopsy, and of the role of neoadjuvant therapy using imatinib prior to surgical treatment. Conclusions: Although isolated cases of coexisting GISTs and prostatic adenocarcinomas have reviously been described, this is the first reported case in the medical literature of a collision tumour involving a rectal GIST and prostatic adenocarcinoma components.

MW, Medical Watches

My project is a business plan about the set up of a company and the development of a new and innovative product aimed for the elders. I decide do this project when I discover that one of the more important needs that have the elders is to remember the medicines that they have to take. I thought that a good way could be through a smart watch. My watch have an only function, is a cheap device, easy to use, easy to understand and easy to set up, because the elders usually do not know to use complex electronics devices. There are other similar smart watches and other devices but do not have the necessary characteristics to be a good reminder for elders. My watch is centred to improve the life of the elders, but my product could also be useful for ill people who have to take many medicines during the day. After realizing this business plan, I have proved that my company is viable in the environment and profitable in the market.

Towards Application of One-Class Classification Methods to Medical Data

In the problem of one-class classification (OCC) one of the classes, the target class, has to be distinguished from all other possible objects, considered as nontargets. In many biomedical problems this situation arises, for example, in diagnosis, image based tumor recognition or analysis of electrocardiogram data. In this paper an approach to OCC based on a typicality test is experimentally compared with reference state-of-the-art OCC techniques-Gaussian, mixture of Gaussians, naive Parzen, Parzen, and support vector data description-using biomedical data sets. We evaluate the ability of the procedures using twelve experimental data sets with not necessarily continuous data. As there are few benchmark data sets for one-class classification, all data sets considered in the evaluation have multiple classes. Each class in turn is considered as the target class and the units in the other classes are considered as new units to be classified. The results of the comparison show the good performance of the typicality approach, which is available for high dimensional data; it is worth mentioning that it can be used for any kind of data (continuous, discrete, or nominal), whereas state-of-the-art approaches application is not straightforward when nominal variables are present.