AIMC Topic: Predictive Value of Tests

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Advancements in opportunistic intracranial aneurysm screening: The impact of a deep learning algorithm on radiologists' analysis of T2-weighted cranial MRI.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
(1) Background: Unruptured Intracranial Aneurysms (UIAs) are common blood vessel malformations, occurring in up to 3 % of healthy adults. Magnetic Resonance Angiography (MRA) is frequently used for the screening of UIAs due to its high resolution in ...

Diagnostic accuracy of artificial intelligence-assisted caries detection: a clinical evaluation.

BMC oral health
OBJECTIVE: This clinical study aimed to evaluate the practical value of integrating an AI diagnostic model into clinical practice for caries detection using intraoral images.

Prediction of gestational diabetes mellitus by multiple biomarkers at early gestation.

BMC pregnancy and childbirth
BACKGROUND: It remains unclear which early gestational biomarkers can be used in predicting later development of gestational diabetes mellitus (GDM). We sought to identify the optimal combination of early gestational biomarkers in predicting GDM in m...

Investigating artificial intelligence models for predicting joint pain from serum biochemistry.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVE: The study used machine learning models to predict the clinical outcome with various attributes or when the models chose features based on their algorithms.

Artificial Intelligence Algorithm Can Predict Lymph Node Malignancy from Endobronchial Ultrasound Transbronchial Needle Aspiration Images for Non-Small Cell Lung Cancer.

Respiration; international review of thoracic diseases
INTRODUCTION: Endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) for lung cancer staging is operator dependent, resulting in high rates of non-diagnostic lymph node (LN) samples. We hypothesized that an artificial intelligence (AI)...

Image-based ECG analyzing deep-learning algorithm to predict biological age and mortality risks: interethnic validation.

Journal of cardiovascular medicine (Hagerstown, Md.)
BACKGROUND: Cardiovascular risk assessment is a critical component of healthcare, guiding preventive and therapeutic strategies. In this study, we developed and evaluated an image-based electrocardiogram (ECG) analyzing an artificial intelligence (AI...

Predictive performance of urinalysis for urine culture results according to causative microorganisms: an integrated analysis with artificial intelligence.

Journal of clinical microbiology
Urinary tract infections (UTIs) are pervasive and prevalent in both community and hospital settings. Recent trends in the changes of the causative microorganisms in these infections could affect the effectiveness of urinalysis (UA). We aimed to evalu...

Automated biventricular quantification in patients with repaired tetralogy of Fallot using a three-dimensional deep learning segmentation model.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Deep learning is the state-of-the-art approach for automated segmentation of the left ventricle (LV) and right ventricle (RV) in cardiovascular magnetic resonance (CMR) images. However, these models have been mostly trained and validated ...

Machine learning algorithms to predict mild cognitive impairment in older adults in China: A cross-sectional study.

Journal of affective disorders
OBJECTIVE: This study aimed to explore the predictive value of machine learning (ML) in mild cognitive impairment (MCI) among older adults in China and to identify important factors causing MCI.