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View article: Machine Learning for Prediction of High‐Risk Hospitalizations in Lymphoma Patients: A Danish Population‐Based Study
Machine Learning for Prediction of High‐Risk Hospitalizations in Lymphoma Patients: A Danish Population‐Based Study Open
Objective Infections are a leading cause of hospitalization in patients treated for lymphoma and can be life‐threatening. This study developed a machine learning (ML)‐based risk stratification method to classify infection‐related hospitali…
View article: Polypharmacy independently predicts survival, hospitalization, and infections in patients with lymphoid cancer
Polypharmacy independently predicts survival, hospitalization, and infections in patients with lymphoid cancer Open
Polypharmacy is a result of multimorbidity and may limit treatment options in patients with lymphoid cancer (LC). To investigate the clinical impact of polypharmacy, we gathered a prediagnostic 1‐year medication history from the Danish pre…
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: 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: Maintaining Transient Diversity Is a General Principle for Improving Collective Problem Solving
Maintaining Transient Diversity Is a General Principle for Improving Collective Problem Solving Open
Humans regularly solve complex problems in cooperative teams. A wide range of mechanisms have been identified that improve the quality of solutions achieved by those teams on reaching consensus. We argue that many of these mechanisms work …
View article: Maintaining transient diversity is a general principle for improving collective problem solving
Maintaining transient diversity is a general principle for improving collective problem solving Open
Humans regularly solve complex problems in cooperative teams. A wide range of mechanisms have been identified that improve the quality of solutions achieved by those teams upon reaching consensus. We argue that many of these mechanisms wor…