AIMC Topic: Artificial Intelligence

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Does artificial intelligence for classifying ultrasound imaging generalize between different populations and contexts?

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology

Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training.

Journal of digital imaging
Artificial intelligence (AI) holds much promise for enabling highly desired imaging diagnostics improvements. One of the most limiting bottlenecks for the development of useful clinical-grade AI models is the lack of training data. One aspect is the ...

Large-scale assessment of consistency in sleep stage scoring rules among multiple sleep centers using an interpretable machine learning algorithm.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: Polysomnography is the gold standard in identifying sleep stages; however, there are discrepancies in how technicians use the standards. Because organizing meetings to evaluate this discrepancy and/or reach a consensus among multipl...

Application of Artificial Intelligence in Gastrointestinal Endoscopy.

Journal of clinical gastroenterology
Artificial intelligence (AI), also known as computer-aided diagnosis, is a technology that enables machines to process information and functions at or above human level and has great potential in gastrointestinal endoscopy applications. At present, t...

Concordance analysis of intrapartum cardiotocography between physicians and artificial intelligence-based technique using modified one-dimensional fully convolutional networks.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: Cardiotocography is a common method of electronic fetal monitoring (EFM) for fetal well-being. Data-driven analyses have shown potential for automated EFM assessment. For this preliminary study, we used a novel artificial intelligence met...

Artificial intelligence neuropathologist for glioma classification using deep learning on hematoxylin and eosin stained slide images and molecular markers.

Neuro-oncology
BACKGROUND: Pathological diagnosis of glioma subtypes is essential for treatment planning and prognosis. Standard histological diagnosis of glioma is based on postoperative hematoxylin and eosin stained slides by neuropathologists. With advancing art...

PV[O]H: Noninvasive Enabling Technology, New Physiological Monitoring, and Big Data.

Military medicine
INTRODUCTION: Measures of normal and abnormal physiology are interrelated and vary continuously. Our ability to detect and predict changes in physiology in real time has been limited in part by the requirement for blood sampling and the lack of a con...