Integrated diagnostics: a conceptual framework with examples
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Anant Madabhushi
Abstract
With the advent of digital pathology, imaging scientists have begun to develop computerized image analysis algorithms for making diagnostic (disease presence), prognostic (outcome prediction), and theragnostic (choice of therapy) predictions from high resolution images of digitized histopathology. One of the caveats to developing image analysis algorithms for digitized histopathology is the ability to deal with highly dense, information rich datasets; datasets that would overwhelm most computer vision and image processing algorithms. Over the last decade, manifold learning and non-linear dimensionality reduction schemes have emerged as popular and powerful machine learning tools for pattern recognition problems. However, these techniques have thus far been applied primarily to classification and analysis of computer vision problems (e.g., face detection). In this paper, we discuss recent work by a few groups in the application of manifold learning methods to problems in computer aided diagnosis, prognosis, and theragnosis of digitized histopathology. In addition, we discuss some exciting recent developments in the application of these methods for multi-modal data fusion and classification; specifically the building of meta-classifiers by fusion of histological image and proteomic signatures for prostate cancer outcome prediction.
Clin Chem Lab Med 2010;48:989–98.
©2010 by Walter de Gruyter Berlin New York
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Articles in the same Issue
- HIGHLIGHT: LABORATORY DIAGNOSTICS IN THE THIRD MILLENIUM: WHERE, HOW AND WHY
- Editorial
- Foreword
- Reviews
- Roots, development and future directions of laboratory medicine
- The “hospital central laboratory”: automation, integration and clinical usefulness
- Clinical pathology services: remapping our strategic itinerary
- Stat laboratory testing: integration or autonomy?
- Point-of-care testing in critical care: the clinician's point of view
- Reproductive-endocrine point-of-care testing: current status and limitations
- Laboratory testing in pharmacies
- Laboratory testing during critical care transport: point-of-care testing in air ambulances
- Self-monitoring of blood glucose with a focus on analytical quality: an overview
- Molecular diagnostics: between chips and customized medicine
- Evaluating laboratory diagnostic tests and translational research
- Integrated diagnostics: a conceptual framework with examples
- General Clinical Chemistry and Laboratory Medicine
- The European Register of Specialists in Clinical Chemistry and Laboratory Medicine: Guide to the Register, Version 3-2010
- The prevalence of preanalytical errors in a Croatian ISO 15189 accredited laboratory
- Indicators and quality specifications for strategic and support processes related to the clinical laboratory: four years' experience
- SKML-Quality Mark for point-of-care test (POCT) glucose meters and glucose meters for home-use
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- Evaluation of the TEST 1 erythrocyte sedimentation rate system and intra- and inter-laboratory quality control using new latex control materials
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