OBJECTIVES: To predict cavernous sinus (CS) invasion by pituitary adenomas (PAs) pre-operatively using a radiomics method based on contrast-enhanced T1 (CE-T1) and T2-weighted magnetic resonance (MR) imaging.
Purpose To develop and validate a deep learning-based automatic detection algorithm (DLAD) for malignant pulmonary nodules on chest radiographs and to compare its performance with physicians including thoracic radiologists. Materials and Methods For ...
Cancer communications (London, England)
Sep 25, 2018
BACKGROUND: Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for malignancy identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal mali...
OBJECTIVE: Efficient allocation of resources in the healthcare system enables providers to care for more and needier patients. Identifying drivers of total charges for transsphenoidal surgery (TSS) for pituitary tumors, which are poorly understood, r...
OBJECTIVE: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizophrenia. Previous machine learning applications suggest that individual classification is feasible and reliable and, however, is focused on the predicti...
INTRODUCTION: Sepsis is associated to a high mortality rate, and its severity must be evaluated quickly. The severity of illness scores used are intended to be applicable to all patient populations, and generally evaluate in-hospital mortality. Howev...
IEEE journal of biomedical and health informatics
Sep 20, 2018
This paper proposes deep learning methods with signal alignment that facilitate the end-to-end classification of raw electrocardiogram (ECG) signals into heartbeat types, i.e., normal beat or different types of arrhythmias. Time-domain sample points ...
The application of machine learning in medicine has been productive in multiple fields, but has not previously been applied to analyze the complexity of organ involvement by chronic graft--host disease. Chronic graft--host disease is classified by an...
PURPOSE: The confusion of MRI sequence names could be solved if MR images were automatically identified after image data acquisition. We revealed the ability of deep learning to classify head MRI sequences.
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Sep 19, 2018
PURPOSE: To explore the social impact of, comfort with, and negative attitudes towards robots among young, middle-aged, and older adults in the United States.
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