AIMC Topic: Humans

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Quantization of extraoral free flap monitoring for venous congestion with deep learning integrated iOS applications on smartphones: a diagnostic study.

International journal of surgery (London, England)
BACKGROUND: Free flap monitoring is essential for postmicrosurgical management and outcomes but traditionally relies on human observers; the process is subjective and qualitative and imposes a heavy burden on staffing. To scientifically monitor and q...

Hierarchical Perception Adversarial Learning Framework for Compressed Sensing MRI.

IEEE transactions on medical imaging
The long acquisition time has limited the accessibility of magnetic resonance imaging (MRI) because it leads to patient discomfort and motion artifacts. Although several MRI techniques have been proposed to reduce the acquisition time, compressed sen...

FedDM: Federated Weakly Supervised Segmentation via Annotation Calibration and Gradient De-Conflicting.

IEEE transactions on medical imaging
Weakly supervised segmentation (WSS) aims to exploit weak forms of annotations to achieve the segmentation training, thereby reducing the burden on annotation. However, existing methods rely on large-scale centralized datasets, which are difficult to...

Natural Language Processing of Nursing Notes: An Integrative Review.

Computers, informatics, nursing : CIN
Natural language processing includes a variety of techniques that help to extract meaning from narrative data. In healthcare, medical natural language processing has been a growing field of study; however, little is known about its use in nursing. We...

Application of Artificial Intelligence in Oncology Nursing: A Scoping Review.

Cancer nursing
BACKGROUND: Artificial intelligence (AI) has been increasingly used in healthcare during the last decade, and recent applications in oncology nursing have shown great potential in improving care for patients with cancer. It is timely to comprehensive...

Federated AI, Current State, and Future Potential.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Artificial intelligence and machine learning applications are becoming increasingly popular in health care and medical devices. The development of accurate machine learning algorithms requires large quantities of good and diverse data. This poses a c...

Automatic Classification of Slit-Lamp Photographs by Imaging Illumination.

Cornea
PURPOSE: The aim of this study was to facilitate deep learning systems in image annotations for diagnosing keratitis type by developing an automated algorithm to classify slit-lamp photographs (SLPs) based on illumination technique.

The Detection of Nasopharyngeal Carcinomas Using a Neural Network Based on Nasopharyngoscopic Images.

The Laryngoscope
OBJECTIVE: To construct and validate a deep convolutional neural network (DCNN)-based artificial intelligence (AI) system for the detection of nasopharyngeal carcinoma (NPC) using archived nasopharyngoscopic images.

Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance.

Japanese journal of radiology
PURPOSE: Neuromelanin-sensitive MRI (NM-MRI) has proven useful for diagnosing Parkinson's disease (PD) by showing reduced signals in the substantia nigra (SN) and locus coeruleus (LC), but requires a long scan time. The aim of this study was to asses...