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Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: In the treatment of ulcerative colitis (UC), an incremental benefit of achieving histologic healing beyond that of endoscopic mucosal healing has been suggested; persistent histologic inflammation increases the risk of exacerbati...

Robotic Assessment of Motor, Sensory, and Cognitive Function in Acute Sport-Related Concussion and Recovery.

Journal of neurotrauma
There is a need for better tools to objectively, reliably, and precisely assess neurological function after sport-related concussion (SRC). The aim of this study was to use a robotic device (Kinesiological Instrument for Normal and Altered Reaching M...

Artificial neural network algorithm model as powerful tool to predict acute lung injury following to severe acute pancreatitis.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
OBJECTIVE: The aim of this study is to predict the risk of severe acute pancreatitis (SAP) associated with acute lung injury (ALI) by artificial neural networks (ANNs) model.

Evaluation of a pneumatic surgical robot with dynamic force feedback.

Journal of robotic surgery
Robot-assisted surgery is limited by the lack of haptic feedback and increased operating times. Force scaling adjusts feedback transmitted to the operator through the use of scaling factors. Herein, we investigate how force scaling affects forces exe...

Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images.

European radiology
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.

Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs.

Radiology
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 ...

Using Artificial Intelligence (Watson for Oncology) for Treatment Recommendations Amongst Chinese Patients with Lung Cancer: Feasibility Study.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) is developing quickly in the medical field and can benefit both medical staff and patients. The clinical decision support system Watson for Oncology (WFO) is an outstanding representative AI in the medical fie...

Feasibility Study of Advanced Neural Networks Applied to sEMG-Based Force Estimation.

Sensors (Basel, Switzerland)
To find out the feasibility of different neural networks in sEMG-based force estimation, in this paper, three types of networks, namely convolutional neural network (CNN), long short-term memory (LSTM) network and their combination (C-LSTM) were appl...

Development and validation of an endoscopic images-based deep learning model for detection with nasopharyngeal malignancies.

Cancer communications (London, England)
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...