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View article: The Danish Lymphoid Cancer Research (DALY-CARE) Data Resource: The Basis for Developing Data-Driven Hematology
The Danish Lymphoid Cancer Research (DALY-CARE) Data Resource: The Basis for Developing Data-Driven Hematology Open
The DALY-CARE data resource allows for the development of near real-time decision-support tools and extrapolation of clinical trial results to clinical practice, thereby improving care for patients with LC while facilitating streamlining o…
View article: Bias in Danish Medical Notes: Infection Classification of Long Texts Using Transformer and LSTM Architectures Coupled with BERT
Bias in Danish Medical Notes: Infection Classification of Long Texts Using Transformer and LSTM Architectures Coupled with BERT Open
Medical notes contain a wealth of information related to diagnosis, prognosis, and overall patient care that can be used to help physicians make informed decisions. However, like any other data sets consisting of data from diverse demograp…
View article: Deployment and validation of the CLL treatment infection model adjoined to an EHR system
Deployment and validation of the CLL treatment infection model adjoined to an EHR system Open
Research algorithms are seldom externally validated or integrated into clinical practice, leaving unknown challenges in deployment. In such efforts, one needs to address challenges related to data harmonization, the performance of an algor…
View article: The Danish Lymphoid Cancer Research (DALY-CARE) data resource: the basis for developing data-driven hematology
The Danish Lymphoid Cancer Research (DALY-CARE) data resource: the basis for developing data-driven hematology Open
Lymphoid-lineage cancers (LC: lymphoma, chronic lymphocytic leukemia, multiple myeloma, and their precursors) share many epidemiological and clinical features. To develop data-driven hematology, we gathered electronic health data and creat…
View article: P629: THE CLL TREATMENT INFECTION MODEL – CLINICAL PROSPECTIVE VALIDATION AS PART OF THE PREVENT-ACALL TRIAL
P629: THE CLL TREATMENT INFECTION MODEL – CLINICAL PROSPECTIVE VALIDATION AS PART OF THE PREVENT-ACALL TRIAL Open
Background: Infections are the major concern for patients with Chronic Lymphocytic Leukemia (CLL). Serious infections (1-month mortality rate: 10%) occur more frequently than progression to CLL treatment. We therefore developed the machine…
View article: Author Correction: Early stimulated immune responses predict clinical disease severity in hospitalized COVID-19 patients
Author Correction: Early stimulated immune responses predict clinical disease severity in hospitalized COVID-19 patients Open
View article: Implementation of the CLL Treatment Infection Model Adjoined to an Electronic Health Record System - Guidelines for Practical Implementation of Data-Driven Models
Implementation of the CLL Treatment Infection Model Adjoined to an Electronic Health Record System - Guidelines for Practical Implementation of Data-Driven Models Open
View article: Early stimulated immune responses predict clinical disease severity in hospitalized COVID-19 patients
Early stimulated immune responses predict clinical disease severity in hospitalized COVID-19 patients Open
View article: Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning
Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning Open
Interpretable risk assessment of SARS-CoV-2 positive patients can aid clinicians to implement precision medicine. Here we trained a machine learning model to predict mortality within 12 weeks of a first positive SARS-CoV-2 test. By leverag…
View article: Prediction of clinical outcome in CLL based on recurrent gene mutations, CLL-IPI variables, and (para)clinical data
Prediction of clinical outcome in CLL based on recurrent gene mutations, CLL-IPI variables, and (para)clinical data Open
A highly variable clinical course, immune dysfunction, and a complex genetic blueprint pose challenges for treatment decisions and the management of risk of infection in patients with chronic lymphocytic leukemia (CLL). In recent years, th…
View article: Identifying patients with chronic lymphocytic leukemia without need of treatment: End of endless watch and wait?
Identifying patients with chronic lymphocytic leukemia without need of treatment: End of endless watch and wait? Open
Introduction Early‐stage chronic lymphocytic leukemia (CLL) challenges specialized management and follow‐up. Methods We developed and validated a prognostic index to identify newly diagnosed patients without need of treatment (CLL‐WONT) by…
View article: Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning
Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning Open
Interpretable risk assessment of SARS-CoV-2 positive patients can aid clinicians to implement precision medicine. Here we trained a machine learning model to predict mortality within 12 weeks of a first positive SARS-CoV-2 test. By leverag…
View article: Machine learning can identify newly diagnosed patients with CLL at high risk of infection
Machine learning can identify newly diagnosed patients with CLL at high risk of infection Open