AIMC Topic: Humans

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Image synthesis of monoenergetic CT image in dual-energy CT using kilovoltage CT with deep convolutional generative adversarial networks.

Journal of applied clinical medical physics
PURPOSE: To synthesize a dual-energy computed tomography (DECT) image from an equivalent kilovoltage computed tomography (kV-CT) image using a deep convolutional adversarial network.

Dynamic Detection of Delayed Cerebral Ischemia: A Study in 3 Centers.

Stroke
BACKGROUND AND PURPOSE: Delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage negatively impacts long-term recovery but is often detected too late to prevent damage. We aim to develop hourly risk scores using routinely collected cl...

Design and Comparison of Magnetically-Actuated Dexterous Forceps Instruments for Neuroendoscopy.

IEEE transactions on bio-medical engineering
Robot-assisted minimally invasive surgical (MIS) techniques offer improved instrument precision and dexterity, reduced patient trauma and risk, and promise to lessen the skill gap among surgeons. These approaches are common in general surgery, urolog...

Machine Learning in Arrhythmia and Electrophysiology.

Circulation research
Machine learning (ML), a branch of artificial intelligence, where machines learn from big data, is at the crest of a technological wave of change sweeping society. Cardiovascular medicine is at the forefront of many ML applications, and there is a si...

Early risk assessment for COVID-19 patients from emergency department data using machine learning.

Scientific reports
Since its emergence in late 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with more than 55 million reported cases and 1.3 million estimated deaths worldwide. While epidemiological and clinical character...

Bioinspired multisensory neural network with crossmodal integration and recognition.

Nature communications
The integration and interaction of vision, touch, hearing, smell, and taste in the human multisensory neural network facilitate high-level cognitive functionalities, such as crossmodal integration, recognition, and imagination for accurate evaluation...

FOPR test: a virtual reality-based technique to assess field of perception and field of regard in hemispatial neglect.

Journal of neuroengineering and rehabilitation
BACKGROUND: We previously proposed a novel virtual reality-based method to assess human field of perception (FOP) and field of regard (FOR), termed the FOPR test. This study assessed the diagnostic validity of the FOPR test for hemispatial neglect (H...

Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning.

BMC infectious diseases
BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a global pandemic that has raised worldwide concern. This study aims to investigate the correlation between the extent of lung infection and relevant clinical laboratory testing indicators in...

Machining learning predicts the need for escalated care and mortality in COVID-19 patients from clinical variables.

International journal of medical sciences
This study aimed to develop a machine learning algorithm to identify key clinical measures to triage patients more effectively to general admission versus intensive care unit (ICU) admission and to predict mortality in COVID-19 pandemic. This retro...

Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response.

Frontiers in immunology
Predictive models are becoming more and more commonplace as tools for candidate antigen discovery to meet the challenges of enabling epitope mapping of cohorts with diverse HLA properties. Here we build on the concept of using two key parameters, div...