AIMC Topic: Humans

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Cone-Beam CT-Guided Transarterial Tagging of Endophytic Renal Tumors with Indocyanine Green for Robot-Assisted Partial Nephrectomy.

Journal of vascular and interventional radiology : JVIR
PURPOSE: To evaluate the safety, efficacy, and clinical impact of preoperative cone-beam computed tomography (CT)-guided selective embolization of endophytic renal tumors with the fluorescent dye indocyanine green (ICG) and ethiodized oil in patients...

Deep neural networks and image classification in biological vision.

Vision research
In this paper we consider recent advances in the use of deep convolutional neural networks to understanding biological vision. We focus on claims about the plausibility of feedforward deep convolutional neural networks (fDCNNs) as models of image cla...

Self-supervised learning via cluster distance prediction for operating room context awareness.

International journal of computer assisted radiology and surgery
PURPOSE: Semantic segmentation and activity classification are key components to create intelligent surgical systems able to understand and assist clinical workflow. In the operating room, semantic segmentation is at the core of creating robots aware...

Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans.

Radiology
Background After severe traumatic brain injury (sTBI), physicians use long-term prognostication to guide acute clinical care yet struggle to predict outcomes in comatose patients. Purpose To develop and evaluate a prognostic model combining deep lear...

Applications of natural language processing in radiology: A systematic review.

International journal of medical informatics
BACKGROUND: Recent advances in performance of natural language processing (NLP) techniques have spurred wider use and more sophisticated applications of NLP in radiology. This study systematically reviews the trends and applications of NLP in radiolo...

Deep learning signatures reveal multiscale intratumor heterogeneity associated with biological functions and survival in recurrent nasopharyngeal carcinoma.

European journal of nuclear medicine and molecular imaging
PURPOSE: How to discriminate different risks of recurrent nasopharyngeal carcinoma (rNPC) patients and guide individual treatment has become of great importance. This study aimed to explore the associations between deep learning signatures and biolog...

Predicting exclusive breastfeeding in maternity wards using machine learning techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Adequate support in maternity wards is decisive for breastfeeding outcomes during the first year of life. Quality improvement interventions require the identification of the factors influencing hospital benchmark indicators....

Multilabel classification of medical concepts for patient clinical profile identification.

Artificial intelligence in medicine
BACKGROUND: The development of electronic health records has provided a large volume of unstructured biomedical information. Extracting patient characteristics from these data has become a major challenge, especially in languages other than English.