AIMC Topic: Humans

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First clinical experience with single-port robotic transanal minimally invasive surgery (SP rTAMIS) for benign rectal neoplasms.

Techniques in coloproctology
BACKGROUND: The new da Vinci Single-Port (SP) robot is a single-arm four-channel robotic system well suited for endoluminal surgery. We report our initial experience performing SP robotic transanal minimally invasive surgery (SP rTAMIS) for rectal ne...

Automatic classification of scanned electronic health record documents.

International journal of medical informatics
OBJECTIVES: Electronic Health Records (EHRs) contain scanned documents from a variety of sources such as identification cards, radiology reports, clinical correspondence, and many other document types. We describe the distribution of scanned document...

Prediction of pedestrian-vehicle conflicts at signalized intersections based on long short-term memory neural network.

Accident; analysis and prevention
Pedestrian protection is an important component of road safety. Intersections are dangerous locations for pedestrians with mixed traffic. This paper aims to predict potential traffic conflicts between pedestrians and vehicles at signalized intersecti...

A deep learning approach to generate synthetic CT in low field MR-guided adaptive radiotherapy for abdominal and pelvic cases.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Artificial intelligence (AI) can play a significant role in Magnetic Resonance guided Radiotherapy (MRgRT), especially to speed up the online adaptive workflow. The aim of this study is to set up a Deep Learning (DL) approach able to generat...

Wearable Biofeedback Improves Human-Robot Compliance during Ankle-Foot Exoskeleton-Assisted Gait Training: A Pre-Post Controlled Study in Healthy Participants.

Sensors (Basel, Switzerland)
The adjunctive use of biofeedback systems with exoskeletons may accelerate post-stroke gait rehabilitation. Wearable patient-oriented human-robot interaction-based biofeedback is proposed to improve patient-exoskeleton compliance regarding the intera...

Testing a convolutional neural network-based hippocampal segmentation method in a stroke population.

Human brain mapping
As stroke mortality rates decrease, there has been a surge of effort to study poststroke dementia (PSD) to improve long-term quality of life for stroke survivors. Hippocampal volume may be an important neuroimaging biomarker in poststroke dementia, a...

Predicting alcohol dependence from multi-site brain structural measures.

Human brain mapping
To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored ...

Development of a prognostic model for mortality in COVID-19 infection using machine learning.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Coronavirus disease 2019 (COVID-19) is a novel disease resulting from infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has quickly risen since the beginning of 2020 to become a global pandemic. As a result of the rap...

Predicting adverse drug reactions of two-drug combinations using structural and transcriptomic drug representations to train an artificial neural network.

Chemical biology & drug design
Adverse drug reactions (ADRs) are pharmacological events triggered by drug interactions with various sources of origin including drug-drug interactions. While there are many computational studies that explore models to predict ADRs originating from s...