AI Medical Compendium Topic:
Predictive Value of Tests

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Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.

Hypertension research : official journal of the Japanese Society of Hypertension
In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hypertension (PIH) is important for both identifying high-risk women and adopting early intervention. In this study, we used four machine-learning models (...

High-Speed On-Site Deep Learning-Based FFR-CT Algorithm: Evaluation Using Invasive Angiography as the Reference Standard.

AJR. American journal of roentgenology
Estimation of fractional flow reserve from coronary CTA (FFR-CT) is an established method of assessing the hemodynamic significance of coronary lesions. However, clinical implementation has progressed slowly, partly because of off-site data transfer...

A machine learning approach for the diagnosis of obstructive sleep apnoea using oximetry, demographic and anthropometric data.

Singapore medical journal
INTRODUCTION: Obstructive sleep apnoea (OSA) is a serious but underdiagnosed condition. Demand for the gold standard diagnostic polysomnogram (PSG) far exceeds its availability. More efficient diagnostic methods are needed, even in tertiary settings....

The three-dimensional weakly supervised deep learning algorithm for traumatic splenic injury detection and sequential localization: an experimental study.

International journal of surgery (London, England)
BACKGROUND: Splenic injury is the most common solid visceral injury in blunt abdominal trauma, and high-resolution abdominal computed tomography (CT) can adequately detect the injury. However, these lethal injuries sometimes have been overlooked in c...

Deep Learning on Bone Scintigraphy to Detect Abnormal Cardiac Uptake at Risk of Cardiac Amyloidosis.

JACC. Cardiovascular imaging
BACKGROUND: Cardiac uptake on technetium-99m whole-body scintigraphy (WBS) is almost pathognomonic of transthyretin cardiac amyloidosis. The rare false positives are often related to light-chain cardiac amyloidosis. However, this scintigraphic featur...

A deep learning model based on contrast-enhanced computed tomography for differential diagnosis of gallbladder carcinoma.

Hepatobiliary & pancreatic diseases international : HBPD INT
BACKGROUND: Gallbladder carcinoma (GBC) is highly malignant, and its early diagnosis remains difficult. This study aimed to develop a deep learning model based on contrast-enhanced computed tomography (CT) images to assist radiologists in identifying...

Coronary X-ray angiography segmentation using Artificial Intelligence: a multicentric validation study of a deep learning model.

The international journal of cardiovascular imaging
INTRODUCTION: We previously developed an artificial intelligence (AI) model for automatic coronary angiography (CAG) segmentation, using deep learning. To validate this approach, the model was applied to a new dataset and results are reported.

How will artificial intelligence transform cardiovascular computed tomography? A conversation with an AI model.

Journal of cardiovascular computed tomography
Artificial intelligence (AI) has the potential to transform healthcare, but its clinical use also has important challenges and limitations. Recently natural language processing and generative pre-training transformer (GPT) models have gained particul...