AIMC Topic: Predictive Value of Tests

Clear Filters Showing 1191 to 1200 of 2336 articles

Challenges Developing Deep Learning Algorithms in Cytology.

Acta cytologica
BACKGROUND: The incorporation of digital pathology into routine pathology practice is becoming more widespread. Definite advantages exist with respect to the implementation of artificial intelligence (AI) and deep learning in pathology, including cyt...

Prediction of amyloid β PET positivity using machine learning in patients with suspected cerebral amyloid angiopathy markers.

Scientific reports
Amyloid-β(Aβ) PET positivity in patients with suspected cerebral amyloid angiopathy (CAA) MRI markers is predictive of a worse cognitive trajectory, and it provides insights into the underlying vascular pathology (CAA vs. hypertensive angiopathy) to ...

Predicting vaginal birth after previous cesarean: Using machine-learning models and a population-based cohort in Sweden.

Acta obstetricia et gynecologica Scandinavica
INTRODUCTION: Predicting a woman's probability of vaginal birth after cesarean could facilitate the antenatal decision-making process. Having a previous vaginal birth strongly predicts vaginal birth after cesarean. Delivery outcome in women with only...

An index based on deep learning-measured spleen volume on CT for the assessment of high-risk varix in B-viral compensated cirrhosis.

European radiology
OBJECTIVES: Deep learning enables an automated liver and spleen volume measurements on CT. The purpose of this study was to develop an index combining liver and spleen volumes and clinical factors for detecting high-risk varices in B-viral compensate...

Automated analysis and detection of abnormalities in transaxial anatomical cardiovascular magnetic resonance images: a proof of concept study with potential to optimize image acquisition.

The international journal of cardiovascular imaging
The large number of available MRI sequences means patients cannot realistically undergo them all, so the range of sequences to be acquired during a scan are protocolled based on clinical details. Adapting this to unexpected findings identified early ...

Traditional and New Methods of Bone Age Assessment-An Overview.

Journal of clinical research in pediatric endocrinology
Bone age is one of biological indicators of maturity used in clinical practice and it is a very important parameter of a child’s assessment, especially in paediatric endocrinology. The most widely used method of bone age assessment is by performing a...

Can artificial intelligence distinguish between malignant and benign mediastinal lymph nodes using sonographic features on EBUS images?

Current medical research and opinion
AIMS: This study aimed to develop a new intelligent diagnostic approach using an artificial neural network (ANN). Moreover, we investigated whether the learning-method-guided quantitative analysis approach adequately described mediastinal lymphadenop...

Using Machine Learning to Predict Suicide Attempts in Military Personnel.

Psychiatry research
Identifying predictors of suicide attempts is critical in intervention and prevention efforts, yet finding predictors has proven difficult due to the low base rate and underpowered statistical approaches. The objective of the current study was to use...