Statistical inference on fractals for cancer risk assessment

• Verfasst von: Stehlík, Milan [VerfasserIn]
• Verfasst von: Giebel, Stefan [VerfasserIn]
• Verfasst von: Prostakova, Jekaterina [VerfasserIn]
• Verfasst von: Schenk, Jens-Peter [VerfasserIn]
• Titel: Statistical inference on fractals for cancer risk assessment
• Verf.angabe: Milan Stehlík, Stefan Giebel, Jekaterina Prostakova and Jens Schenk
• E-Jahr: 2014
• Jahr: October 2014
• Umfang: 16 S.
• Fussnoten: Gesehen am 17.07.2020
• Titel Quelle: Enthalten in: Pakistan journal of statistics
• Ort Quelle: Lahore : [Verlag nicht ermittelbar], 1994
• Jahr Quelle: 2014
• Band/Heft Quelle: 30(2014), Seite 439-454
• ISSN Quelle: 2310-3515
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1725091763

Abstract

This paper discusses the application of fractal geometry in medicine. Fractal geometry - is a new tool that can be extremely useful for many problems in almost every scientific - field. The studies recently done in medicine show fractals can be applied for cancer - detection and the description of pathological architecture of tumours. This fact is not - surprising, as due to the irregular structure, cancerous cells can be interpreted as fractals. - Cancer diagnosis can be done via determination of fractal dimension. The intention of - this paper is to demonstrate the potential of testing for the range of fractal dimension. We - briefly discuss recent studies with fractals in medicine, in particular studies concerning - cancer diagnosis. We employ the likelihood ratio test for the Hausdorff dimension and we - empirically check the obtained tests on Sierpinski Carpet and on cancer data. Cancer data - consists of 29 patients who have been diagnosed with renal cancer. In contrast to other - applications on cancer data, we have not to investigate an area of cancerous cells. This - kind of tumour is more typical for small children, therefore, non-invasive methods seem - more important.