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Effectiveness of an Artificial Intelligence-Enabled Intervention for Detecting Clinical Deterioration.

JAMA internal medicine
IMPORTANCE: Inpatient clinical deterioration is associated with substantial morbidity and mortality but may be easily missed by clinicians. Early warning scores have been developed to alert clinicians to patients at high risk of clinical deterioratio...

Deep Learning-based Approach for Brainstem and Ventricular MR Planimetry: Application in Patients with Progressive Supranuclear Palsy.

Radiology. Artificial intelligence
Purpose To develop a fast and fully automated deep learning (DL)-based method for the MRI planimetric segmentation and measurement of the brainstem and ventricular structures most affected in patients with progressive supranuclear palsy (PSP). Materi...

Impact of Deep Learning Image Reconstruction Methods on MRI Throughput.

Radiology. Artificial intelligence
Purpose To evaluate the effect of implementing two distinct commercially available deep learning reconstruction (DLR) algorithms on the efficiency of MRI examinations conducted in real clinical practice within an outpatient setting at a large, multic...

Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan.

Radiology. Artificial intelligence
Purpose To evaluate the impact of an artificial intelligence (AI) assistant for lung cancer screening on multinational clinical workflows. Materials and Methods An AI assistant for lung cancer screening was evaluated on two retrospective randomized m...

Deep Learning Classification of Usual Interstitial Pneumonia Predicts Outcomes.

American journal of respiratory and critical care medicine
Computed tomography (CT) enables noninvasive diagnosis of usual interstitial pneumonia (UIP), but enhanced image analyses are needed to overcome the limitations of visual assessment. Apply multiple instance learning (MIL) to develop an explainable ...

An interpretable machine learning model to predict off-pump coronary artery bypass grafting-associated acute kidney injury.

Advances in clinical and experimental medicine : official organ Wroclaw Medical University
BACKGROUND: Off-pump coronary artery bypass grafting-associated acute kidney injury (OPCAB-AKI) is related to 30-day perioperative mortality. Existing mathematical models cannot be applied to help clinicians make early diagnosis and intervention deci...

Prognostic value of a novel artificial intelligence-based coronary computed tomography angiography-derived ischaemia algorithm for patients with suspected coronary artery disease.

European heart journal. Cardiovascular Imaging
AIMS: Coronary computed tomography angiography (CTA) imaging is used to diagnose patients with suspected coronary artery disease (CAD). A novel artificial intelligence-guided quantitative computed tomography ischaemia algorithm (AI-QCTischaemia) aims...

Artificial intelligence system for automatic maxillary sinus segmentation on cone beam computed tomography images.

Dento maxillo facial radiology
OBJECTIVES: The study aims to develop an artificial intelligence (AI) model based on nnU-Net v2 for automatic maxillary sinus (MS) segmentation in cone beam computed tomography (CBCT) volumes and to evaluate the performance of this model.

Neural Network-Based Prediction of Perceived Sleep Quality Through Wearable Device Data.

Studies in health technology and informatics
BACKGROUND: This study focuses on the development of a neural network model to predict perceived sleep quality using data from wearable devices. We collected various physiological metrics from 18 participants over four weeks, including heart rate, ph...

Machine Learning-Based Prediction of Malnutrition in Surgical In-Patients: A Validation Pilot Study.

Studies in health technology and informatics
BACKGROUND: Malnutrition in hospitalised patients can lead to serious complications, worse patient outcomes and longer hospital stays. State-of-the-art screening methods rely on scores, which need additional manual assessments causing higher workload...