e 2013

Artificial neural networks in medical diagnosis

AMATO, Filippo, Alberto LÓPEZ RODRÍGUEZ, Eladia María PEÑA-MÉNDEZ, Petr VAŇHARA, Aleš HAMPL et. al.

Basic information

Original name

Artificial neural networks in medical diagnosis

Authors

AMATO, Filippo (380 Italy, belonging to the institution), Alberto LÓPEZ RODRÍGUEZ (724 Spain, belonging to the institution), Eladia María PEÑA-MÉNDEZ (724 Spain), Petr VAŇHARA (203 Czech Republic, belonging to the institution), Aleš HAMPL (203 Czech Republic, belonging to the institution) and Josef HAVEL (203 Czech Republic, guarantor, belonging to the institution)

Edition

12 pp. 2013

Publisher

University of South Bohemia

Other information

Language

English

Type of outcome

Přehledové a vzdělávací texty

Field of Study

10406 Analytical chemistry

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 1.775

RIV identification code

RIV/00216224:14110/13:00080563

Organization unit

Faculty of Medicine

ISSN

DOI

UT WoS

000314809600001

Keywords in English

medical diagnosis; artificial intelligence; artificial neural networks; cancer; cardiovascular diseases; diabetes
Změněno: 30/8/2018 13:24, Mgr. Michal Petr

Abstract

V originále

An extensive amount of information is currently available to clinical specialists, ranging from details of clinical symptoms to various types of biochemical data and outputs of imaging devices. Each type of data provides information that must be evaluated and assigned to a particular pathology during the diagnostic process. To streamline the diagnostic process in daily routine and avoid misdiagnosis, artificial intelligence methods (especially computer aided diagnosis and artificial neural networks) can be employed. These adaptive learning algorithms can handle diverse types of medical data and integrate them into categorized outputs. In this paper, we briefly review and discuss the philosophy, capabilities, and limitations of artificial neural networks in medical diagnosis through selected examples.

Links

EE2.3.20.0185, research and development project
Name: Centrum analýz a modelování tkání a orgánů
GA202/07/1669, research and development project
Name: Depozice termomechanicky stabilních nanostrukturovaných diamantu-podobných tenkých vrstev ve dvojfrekvenčních kapacitních výbojích
Investor: Czech Science Foundation, Deposition of thermomehanically stable nanostructured diamond-like thin films in dual frequency capacitive discharges
MSM0021622411, plan (intention)
Name: Studium a aplikace plazmochemických reakcí v neizotermickém nízkoteplotním plazmatu a jeho interakcí s povrchem pevných látek
Investor: Ministry of Education, Youth and Sports of the CR, Study and application of plasma chemical reactions in non-isothermic low temperature plasma and its interaction with solid surface
MSM0021622430, plan (intention)
Name: Funkční a molekulární charakteristiky nádorových a normálních kmenových buněk - identifikace cílů pro nová terapeutika a terapeutické strategie
Investor: Ministry of Education, Youth and Sports of the CR, Functional and molecular characteristics of cancer and normal stem cells - identification of targets for novel therapeutics and therapeutic strategies