Artificial intelligence in imaging: the radiologist's role

DL Rubin - Journal of the American College of Radiology, 2019 - Elsevier
Rapid technological advancements in artificial intelligence (AI) methods have fueled
explosive growth in decision tools being marketed by a rapidly growing number of …

Improving the visual communication of environmental model projections

HJ Bannister, PG Blackwell, K Hyder, TJ Webb - Scientific Reports, 2021 - nature.com
Environmental and ecosystem models can help to guide management of changing natural
systems by projecting alternative future states under a common set of scenarios. Combining …

The performance of pre-delivery serum concentrations of angiogenic factors in predicting postpartum antihypertensive drug therapy following abdominal delivery in …

NC Ngene, J Moodley, T Naicker - PLoS One, 2019 - journals.plos.org
Background The imbalance between circulating concentrations of anti-and pro-angiogenic
factors is usually intense in preeclampsia with severe features (sPE). It is possible that pre …

Increase Trichomonas vaginalis detection based on urine routine analysis through a machine learning approach

HY Wang, CC Hung, CH Chen, TY Lee, KY Huang… - Scientific reports, 2019 - nature.com
Trichomonas vaginalis (T. vaginalis) detection remains an unsolved problem in using of
automated instruments for urinalysis. The study proposes a machine learning (ML)-based …

The gray zone of thyroid nodules: Using a nomogram to provide malignancy risk assessment and guide patient management

E Yousefi, GH Sura, J Somma - Cancer medicine, 2021 - Wiley Online Library
Background Thyroid nodules have a low prevalence of malignancy and most proven
cancers do not behave aggressively. Thus, risk‐stratification of nodules is a critical step to …

Systematic error detection in laboratory medicine

A Momeni-Boroujeni, MR Pincus - Quality Control in Laboratory, 2018 - books.google.com
Measurements in laboratory medicine have a degree of uncertainty; this uncertainty is often
called “error” and refers to imprecisions and inaccuracies in measurement. This …

Logistic regression with machine learning sheds light on the problematic sexual behavior phenotype

S Jiang, K Wallace, E Yang, L Roper… - Journal of Addiction …, 2023 - journals.lww.com
Objectives There has been a longstanding debate about whether the mechanisms involved
in problematic sexual behavior (PSB) are similar to those observed in addictive disorders, or …

A Bayesian method for safety signal detection in ongoing blinded randomised controlled trials

K Brock, C Chen, S Ho, G Fuller… - Pharmaceutical …, 2023 - Wiley Online Library
Sponsors have a responsibility to minimise risk to participants in clinical studies through
safety monitoring. The FDA Final Rule for IND Safety Reporting requires routine aggregate …

A new way of handling missing data in multi-source classification based on adaptive imputation

I Abdelkhalek, A Ben Brahim, N Essousi - Model and Data Engineering: 8th …, 2018 - Springer
Data fusion is an interesting methodology for improving the classification performance. It
consists in combining data acquired from multiple sources for more informative decision and …

Effects of potential confounding variables on accuracy of a commercially available veterinary point-of-care hematocrit meter in the evaluation of blood samples from …

BAL Thevelein, A Koenig, BM Brainard… - Journal of the …, 2021 - Am Vet Med Assoc
OBJECTIVE To assess the agreement in measurements of Hct values and hemoglobin
(Hgb) concentrations in blood samples from dogs and cats between a commercially …