Hospital-Based Medicine

Risk Management

Latest AI and machine learning research in risk management for healthcare professionals.

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Deep learning based protocol to construct an immune-related gene network of host-pathogen interactions in plants.

Investigating network behavior from host-pathogen interactions is challenging. Here, we present the ...

Zygomatic implant placement using a robot-assisted flapless protocol: proof of concept.

Robotic assistance can help in physically guiding the drilling trajectory during zygomatic implant p...

Reducing Errors Resulting From Commonly Missed Chest Radiography Findings.

Chest radiography (CXR), the most frequently performed imaging examination, is vulnerable to interpr...

An Efficient Approach to Large-Scale Ab Initio Conformational Energy Profiles of Small Molecules.

Accurate conformational energetics of molecules are of great significance to understand maby chemica...

The usability and feasibility validation of the social robot MINI in people with dementia and mild cognitive impairment; a study protocol.

BACKGROUND: Social robots have demonstrated promising outcomes in terms of increasing the social hea...

Protocol for the operation of a breathing and vaping biomimetic robot to delineate real-time inhaled particle profile of electronic cigarettes.

We recently developed a robotic human vaping mimetic real-time particle analyzer (HUMITIPAA) to eval...

A Novel Dynamic Bit Rate Analysis Technique for Adaptive Video Streaming over HTTP Support.

Recently, there has been an increase in research interest in the seamless streaming of video on top ...

3-Dimensional Immunostaining and Automated Deep-Learning Based Analysis of Nerve Degeneration.

Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease driven by inflammation and de...

Protocol to explain graph neural network predictions using an edge-centric Shapley value-based approach.

Here we present EdgeSHAPer, a workflow for explaining graph neural networks by approximating Shapley...

Using artificial intelligence to optimize delivery of weight loss treatment: Protocol for an efficacy and cost-effectiveness trial.

Gold standard behavioral weight loss (BWL) is limited by the availability of expert clinicians and h...

Unified machine learning protocol for copolymer structure-property predictions.

Structure-property relationships are extremely valuable when predicting the properties of polymers. ...

Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation.

Leading a sedentary lifestyle may cause numerous health problems. Therefore, passive lifestyle chang...

Deep Learning-based calculation of patient size and attenuation surrogates from localizer Image: Toward personalized chest CT protocol optimization.

PURPOSE: Extracting water equivalent diameter (DW), as a good descriptor of patient size, from the C...

Body weight-supported gait training for patients with spinal cord injury: a network meta-analysis of randomised controlled trials.

Different body weight-supported gait-training strategies are available for improving ambulation in i...

Nondestructive microbial discrimination using single-cell Raman spectra and random forest machine learning algorithm.

Raman microspectroscopy is a powerful tool for obtaining biomolecular information from single microb...

Overcoming challenges of translating deep-learning models for glioblastoma: the ZGBM consortium.

OBJECTIVE: To report imaging protocol and scheduling variance in routine care of glioblastoma patien...

ognitive utcomes in the ragmatic nvestigation of optimaxygen argets (CO-PILOT) trial: protocol and statistical analysis plan.

INTRODUCTION: Long-term cognitive impairment is one of the most common complications of critical ill...

Objective performance metrics in human robotic neuroendovascular interventions: a scoping review protocol.

OBJECTIVE: The objective of this scoping review is to review the available information on objective ...

Protocol to identify functional doppelgängers and verify biomedical gene expression data using doppelgangerIdentifier.

Functional doppelgängers (FDs) are independently derived sample pairs that confound machine learning...

Deep Learning Segmentation and Reconstruction for CT of Chronic Total Coronary Occlusion.

Background CT imaging of chronic total occlusion (CTO) is useful in guiding revascularization, but m...

Conformal prediction under feedback covariate shift for biomolecular design.

Many applications of machine-learning methods involve an iterative protocol in which data are collec...

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