Results 11 to 20 of about 896,359 (265)
Calibrating variant-scoring methods for clinical decision making. [PDF]
Bioinformatics, 2021 Abstract Summary Identifying pathogenic variants and annotating them is a major challenge in human genetics, especially for the non-coding ones. Several tools have been developed and used to predict the functional effect of genetic variants.
Benevenuta S, Capriotti E, Fariselli P.
europepmc +4 more sources
Diffusion weighted imaging of the breast: Performance of standardized breast tumor tissue selection methods in clinical decision making. [PDF]
PLoS ONE, 2021 ObjectivesIn breast diffusion weighted imaging (DWI) protocol standardization, it is recently shown that no breast tumor tissue selection (BTTS) method outperformed the others.
M Wielema +9 more
doaj +2 more sources
Clinical decision-making at the end of life: a mixed-methods study [PDF]
BMJ Supportive & Palliative Care, 2018 ObjectivesTo improve the ability of clinical staff to recognise end of life in hospital inpatients dying as a result of cancer and heart failure, and to generate new hypotheses for further research.MethodsThis mixed-methods study used decision theory as a theoretical basis. It involved a parallel databases-convergent design, incorporating findings from
Taylor, P., Johnson, M.J., Dowding, D.W.
openaire +5 more sources
From clinical reasoning to effective clinical decision making—new training methods [PDF]
Frontiers in Psychology, 2015 Identification of causes and immediate adjustment to treatment of acute thrombocytopenia occurring in patients in the intensive care unit is required to avoid imminent complications. Hence it is important to train awareness and clinical decision making of students in the medical curriculum.
Wadowski, Patricia P. +3 more
openaire +3 more sources
MACHINE LEARNING METHODS IN CLINICAL DECISION-MAKING
, 2023 MACHINE LEARNING METHODS IN CLINICAL DECISION-MAKING SUMMARY Machine Learning (ML) in clinical practice refers to the application of computational algorithms and statistical models to analyze and interpret medical data for improved decision-making and patient care.
Poluboiartsev, Igor O. +1 more
openaire +2 more sources
Understanding clinical decision-making in mesothelioma care: a mixed methods study
BMJ Open Respiratory Research, 2022 Introduction Malignant pleural mesothelioma is a rare, incurable cancer arising from previous asbestos exposure; patients have a poor prognosis, with a median survival rate of 8–14 months. Variation in mesothelioma clinical decision-making remains common with a lack of multidisciplinary knowledge sharing, leading to
Henshall, C +9 more
openaire +4 more sources
Unintended consequences of machine learning in medicine? [version 1; referees: 2 approved]
F1000Research, 2017 Machine learning (ML) has the potential to significantly aid medical practice. However, a recent article highlighted some negative consequences that may arise from using ML decision support in medicine.
Laura McDonald +3 more
doaj +1 more source
F1000Research, 2018 Background: The newly introduced self-adhering flowable resin-composites decrease the required time for application by incorporation of an acidic adhesive monomer, thus reducing the number of steps, but its bonding is still uncertain.
Tamer M. Hamdy
doaj +1 more source
F1000Research, 2017 Background: The newly introduced self-adhering flowable resin-composites decrease the required time for application by incorporation of an acidic adhesive monomer, thus reducing the number of steps, but its bonding is still uncertain.
Tamer M. Hamdy
doaj +1 more source
F1000Research, 2017 Background: The newly introduced self-adhering flowable resin-composites decrease the required time for application by incorporation of an acidic adhesive monomer, thus reducing the number of the steps, but its bonding is still uncertain. The aim of this
Tamer M. Hamdy
doaj +1 more source