The era of "Personalized Medicine," guided by individual molecular variation in DNA, RNA, expressed proteins and other forms of high volume molecular data brings new requirements and challenges to the design and implementation of Electronic Health Records (EHRs). In this article we describe the characteristics of biomolecular data that differentiate it from other classes of data commonly found in EHRs, enumerate a set of technical desiderata for its management in healthcare settings, and offer a candidate technical approach to its compact and efficient representation in operational systems.
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http://dx.doi.org/10.1016/j.jbi.2011.12.005 | DOI Listing |
Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit
June 2024
Stony Brook University, USA.
Introducing interpretability and reasoning into Multiple Instance Learning (MIL) methods for Whole Slide Image (WSI) analysis is challenging, given the complexity of gigapixel slides. Traditionally, MIL interpretability is limited to identifying salient regions deemed pertinent for downstream tasks, offering little insight to the end-user (pathologist) regarding the rationale behind these selections. To address this, we propose Self-Interpretable MIL (SI-MIL), a method intrinsically designed for interpretability from the very outset.
View Article and Find Full Text PDFBr J Math Stat Psychol
February 2025
Department of Psychology, University of South Carolina, Columbia, South Carolina, USA.
Reliability is an essential measure of how closely observed scores represent latent scores (reflecting constructs), assuming some latent variable measurement model. We present a general theoretical framework of reliability, placing emphasis on measuring the association between latent and observed scores. This framework was inspired by McDonald's (Psychometrika, 76, 511) regression framework, which highlighted the coefficient of determination as a measure of reliability.
View Article and Find Full Text PDFBrief Bioinform
July 2024
Scientific Direction, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi, 53, 00144 Rome, Italy.
Clinical Bioinformatics is a knowledge framework required to interpret data of medical interest via computational methods. This area became of dramatic importance in precision oncology, fueled by cancer genomic profiling: most definitions of Molecular Tumor Boards require the presence of bioinformaticians. However, all available literature remained rather vague on what are the specific needs in terms of digital tools and expertise to tackle and interpret genomics data to assign novel targeted or biomarker-driven targeted therapies to cancer patients.
View Article and Find Full Text PDFJ Biomed Inform
September 2024
Computational Health Informatics Group, Institute of Biomedicine of Seville, IBiS/Virgen del Rocío University Hospital/CSIC/University of Seville, Seville, Spain.
Background: The future European Health Research and Innovation Cloud (HRIC), as fundamental part of the European Health Data Space (EHDS), will promote the secondary use of data and the capabilities to push the boundaries of health research within an ethical and legally compliant framework that reinforces the trust of patients and citizens.
Objective: This study aimed to analyse health data management mechanisms in Europe to determine their alignment with FAIR principles and data discovery generating best. practices for new data hubs joining the HRIC ecosystem.
J Am Med Inform Assoc
August 2024
Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02215, United States.
Objective: To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app "listener" that accesses standardized data across the SMART/HL7 Bulk FHIR Access application programming interface (API).
Methods: We advance a model for scalable, federated, data sharing and learning. Cumulus software is designed to address key technology and policy desiderata including local utility, control, and administrative simplicity as well as privacy preservation during robust data sharing, and artificial intelligence (AI) for processing unstructured text.
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