14 papers · ranked by Valyu relevance
Karel G. M. Moons, Joris A. H. de Groot, Walter Bouwmeester, Yvonne Vergouwe + 4 more
'Yvonne Vergouwe' 'Susan Mallett' 'Douglas G. Altman' 'Johannes B. Reitsma' 'Gary S. Collins'] Carl Moons and colleagues provide a checklist and background explanation for critically appraising and extracting data from systematic reviews of prognostic and diagnostic prediction modelling studies. Please see later in the…
Ricardo J. Pais, Pietro Pinoli, Anna Bernasconi
Clinical bioinformatics is a newly emerging field that applies bioinformatics techniques for facilitating the identification of diseases, discovery of biomarkers, and therapy decision. Mathematical modelling is part of bioinformatics analysis pipelines and a fundamental step to extract clinical insights from genomes…
Shabbar I. Ranapurwala, Joseph E. Cavanaugh, Tracy Young, Hongqian Wu + 2 more
'Hongqian Wu' 'Corinne Peek-Asa' 'Marizen R. Ramirez'] Background The goal of predictive modelling is to identify the likelihood of future events, such as the predictive modelling used in climate science to forecast weather patterns and significant weather occurrences. In public health, increasingly sophisticated…
Daniel Stahl
Machine learning (ML) and prediction modelling have become increasingly influential in healthcare, providing critical insights and supporting clinical decisions, particularly in the age of big data. This paper serves as an introductory guide for health researchers and readers interested in prediction modelling and…
Roemer J Janse, Ameen Abu-Hanna, Iacopo Vagliano, Vianda S Stel + 5 more
'Kitty J Jager' 'Giovanni Tripepi' 'Carmine Zoccali' 'Friedo W Dekker' 'Merel van Diepen'] Title: ABSTRACT An artificial intelligence boom is currently ongoing, mainly due to large language models, leading to significant interest in artificial intelligence and subsequently also in machine learning (ML). One area where…
Philip Greulich
Purpose of Review This article gives a broad overview of quantitative modelling approaches in biology and provides guidance on how to employ them to boost stem cell research, by helping to answer biological questions and to predict the outcome of biological processes. Recent Findings The twenty-first century has seen a…
Gerhard A. Holzapfel, Kevin Linka, Selda Sherifova, Christian J. Cyron
'Christian J. Cyron'] The constitutive modelling of soft biological tissues has rapidly gained attention over the last 20 years. Current constitutive models can describe the mechanical properties of arterial tissue. Predicting these properties from microstructural information, however, remains an elusive goal. To…
Emanuela Barbini, Gabriele Cevenini, Sabino Scolletta, Bonizella Biagioli + 2 more
'Bonizella Biagioli' 'Pierpaolo Giomarelli' 'Paolo Barbini'] Background Different methods have recently been proposed for predicting morbidity in intensive care units (ICU). The aim of the present study was to critically review a number of approaches for developing models capable of estimating the probability of…
Fiona R. Macfarlane, Mark A. J. Chaplain, Raluca Eftimie
Rheumatoid arthritis is a chronic autoimmune disease that is a major public health challenge. The disease is characterised by inflammation of synovial joints and cartilage erosion, which lead to chronic pain, poor life quality and, in some cases, mortality. Understanding the biological mechanisms behind the progression…
Lazaros Belbasis, Orestis A. Panagiotou
The field of health services research studies the health care system by examining outcomes relevant to patients and clinicians but also health economists and policy makers. Such outcomes often include health care spending, and utilization of care services. Building accurate prediction models using reproducible research…
Riddhi Chawla, S. Balaji, Raed N. Alabdali, Ibrahim A. Naguib + 2 more
'Nadir O. Hamed' 'Heba Y. Zahran'] A variety of receptor and donor characteristics influence long-and short-term kidney graft survival. It is critical to predict the effectiveness of kidney transplantation to optimise organ allocation. This would allow patients to choose the best accessible kidney donor and the optimal…
Miljana Milić, Jelena Milojković, Ivan Marković, Petar Nikolić
Accurate prediction of the short time series with highly irregular behavior is a challenging task found in many areas of modern science. Such data fluctuations are not systematic and hardly predictable. In recent years, artificial neural networks have widely been exploited for those purposes. Although it is possible to…
Mark Pogson, Mike Holcombe, Rod Smallwood, Eva Qwarnstrom + 1 more
'Vladimir B. Bajic'] Nature is governed by local interactions among lower-level sub-units, whether at the cell, organ, organism, or colony level. Adaptive system behaviour emerges via these interactions, which integrate the activity of the sub-units. To understand the system level it is necessary to understand the…
Armin Rauschenberger, Enrico Glaab
In many biomedical applications, we are more interested in the predicted probability that a numerical outcome is above a threshold than in the predicted value of the outcome. For example, it might be known that antibody levels above a certain threshold provide immunity against a disease, or a threshold for a disease…