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Risk

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Individualized prediction of psychosis in subjects with an at-risk mental state.

Schizophrenia research
Early intervention strategies in psychosis would significantly benefit from the identification of reliable prognostic biomarkers. Pattern classification methods have shown the feasibility of an early diagnosis of psychosis onset both in clinical and ...

Feature selection through validation and un-censoring of endovascular repair survival data for predicting the risk of re-intervention.

BMC medical informatics and decision making
BACKGROUND: Feature selection (FS) process is essential in the medical area as it reduces the effort and time needed for physicians to measure unnecessary features. Choosing useful variables is a difficult task with the presence of censoring which is...

A machine learning approach to investigate the relationship between shape features and numerically predicted risk of ascending aortic aneurysm.

Biomechanics and modeling in mechanobiology
Geometric features of the aorta are linked to patient risk of rupture in the clinical decision to electively repair an ascending aortic aneurysm (AsAA). Previous approaches have focused on relationship between intuitive geometric features (e.g., diam...

A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The treatment and management of early stage estrogen receptor positive (ER+) breast cancer is hindered by the difficulty in identifying patients who require adjuvant chemotherapy in contrast to those that will respond to hormonal therapy. To distingu...

Predicting Prolonged Stay in the ICU Attributable to Bleeding in Patients Offered Plasma Transfusion.

AMIA ... Annual Symposium proceedings. AMIA Symposium
In blood transfusion studies, plasma transfusion (PPT) and bleeding are known to be associated with risk of prolonged ICU length of stay (ICU-LOS). However, as patients can show significant heterogeneity in response to a treatment, there might exists...

Handling limited datasets with neural networks in medical applications: A small-data approach.

Artificial intelligence in medicine
MOTIVATION: Single-centre studies in medical domain are often characterised by limited samples due to the complexity and high costs of patient data collection. Machine learning methods for regression modelling of small datasets (less than 10 observat...

Quantifying Risk for Anxiety Disorders in Preschool Children: A Machine Learning Approach.

PloS one
Early childhood anxiety disorders are common, impairing, and predictive of anxiety and mood disorders later in childhood. Epidemiological studies over the last decade find that the prevalence of impairing anxiety disorders in preschool children range...

Progesterone supplementation in the early luteal phase after artificial insemination improves conception rates in high-producing dairy cows.

Theriogenology
This study examines the possible effects on the reproductive performance of high-producing dairy cows of progesterone (P4) given in the early luteal phase (1.55 g of P4), from Days 3 to 5 post-artificial insemination (AI) as compared with the time of...