OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 06.05.2026, 22:44

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

Practicing Pathology in the Era of Big Data and Personalized Medicine

2013·59 Zitationen·Applied immunohistochemistry & molecular morphologyOpen Access
Volltext beim Verlag öffnen

59

Zitationen

2

Autoren

2013

Jahr

Abstract

The traditional task of the pathologist is to assist physicians in making the correct diagnosis of diseases at the earliest possible stage to effectuate the optimal treatment strategy for each individual patient. In this respect surgical pathology (the traditional tissue diagnosis) is but a tool. It is not, of itself, the purpose of pathology practice; and change is in the air. This January 2014 issue of Applied Immunohistochemistry and Molecular Morphology (AIMM) embraces that change by the incorporation of the agenda and content of the journal Diagnostic Molecular Morphology (DMP). Over a decade ago AIMM introduced and promoted the concept of "molecular morphology," and has sought to publish molecular studies that correlate with the morphologic features that continue to define cancer and many diseases. That intent is now reinforced and extended by the merger with DMP, as a logical and timely response to the growing impact of a wide range of genetic and molecular technologies that are beginning to reshape the way in which pathology is practiced. The use of molecular and genomic techniques already demonstrates clear value in the diagnosis of disease, with treatment tailored specifically to individual patients. Personalized medicine is the future, and personalized medicine demands personalized pathology. The need for integration of the flood of new molecular data, with surgical pathology, digital pathology, and the full range of pathology data in the electronic medical record has never been greater. This review describes the possible impact of these pressures upon the discipline of pathology, and examines possible outcomes. There is a sense of excitement and adventure. Active adaption and innovation are required. The new AIMM, incorporating DMP, seeks to position itself for a central role in this process.

Ähnliche Arbeiten

Autoren

Institutionen

Themen

Cancer Genomics and DiagnosticsAI in cancer detectionBiomedical Text Mining and Ontologies
Volltext beim Verlag öffnen