AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Area Under Curve

Showing 171 to 180 of 1152 articles

Clear Filters

Deep learning-assisted diagnosis of benign and malignant parotid tumors based on contrast-enhanced CT: a multicenter study.

European radiology
OBJECTIVES: To develop deep learning-assisted diagnosis models based on CT images to facilitate radiologists in differentiating benign and malignant parotid tumors.

A Multidatabase ExTRaction PipEline (METRE) for facile cross validation in critical care research.

Journal of biomedical informatics
Transforming raw EHR data into machine learning model-ready inputs requires considerable effort. One widely used EHR database is Medical Information Mart for Intensive Care (MIMIC). Prior work on MIMIC-III cannot query the updated and improved MIMIC-...

Assessing the utility of a sliding-windows deep neural network approach for risk prediction of trauma patients.

Scientific reports
The risks of post trauma complications are regulated by the injury, comorbidities, and the clinical trajectories, yet prediction models are often limited to single time-point data. We hypothesize that deep learning prediction models can be used for r...

Deep learning augmented ECG analysis to identify biomarker-defined myocardial injury.

Scientific reports
Chest pain is a common clinical complaint for which myocardial injury is the primary concern and is associated with significant morbidity and mortality. To aid providers' decision-making, we aimed to analyze the electrocardiogram (ECG) using a deep c...

A real-time interpretable artificial intelligence model for the cholangioscopic diagnosis of malignant biliary stricture (with videos).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: It is crucial to accurately determine malignant biliary strictures (MBSs) for early curative treatment. This study aimed to develop a real-time interpretable artificial intelligence (AI) system to predict MBSs under digital singl...

Detection of aspiration from images of a videofluoroscopic swallowing study adopting deep learning.

Oral radiology
OBJECTIVES: A videofluoroscopic swallowing study (VFSS) is conducted to detect aspiration. However, aspiration occurs within a short time and is difficult to detect. If deep learning can detect aspirations with high accuracy, clinicians can focus on ...

NeuroPpred-SVM: A New Model for Predicting Neuropeptides Based on Embeddings of BERT.

Journal of proteome research
Neuropeptides play pivotal roles in different physiological processes and are related to different kinds of diseases. Identification of neuropeptides is of great benefit for studying the mechanism of these physiological processes and the treatment of...

DeepFundus: A flow-cytometry-like image quality classifier for boosting the whole life cycle of medical artificial intelligence.

Cell reports. Medicine
Medical artificial intelligence (AI) has been moving from the research phase to clinical implementation. However, most AI-based models are mainly built using high-quality images preprocessed in the laboratory, which is not representative of real-worl...

ANIMAL-SPOT enables animal-independent signal detection and classification using deep learning.

Scientific reports
Bioacoustic research spans a wide range of biological questions and applications, relying on identification of target species or smaller acoustic units, such as distinct call types. However, manually identifying the signal of interest is time-intensi...

Machine-learning-based ground sink susceptibility evaluation using underground pipeline data in Korean urban area.

Scientific reports
Ground subsidence caused by natural factors, including groundwater, has been extensively researched. However, there have been few studies on ground sink caused mainly by artifacts, including underground pipelines in urban areas. This paper proposes a...