Hospital-Based Medicine

Risk Management

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

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Cov_FB3D: A De Novo Covalent Drug Design Protocol Integrating the BA-SAMP Strategy and Machine-Learning-Based Synthetic Tractability Evaluation.

drug design actively seeks to use sets of chemical rules for the fast and efficient identification ...

Machine Learning for Automation of Radiology Protocols for Quality and Efficiency Improvement.

PURPOSE: The aim of this study was to enhance multispecialty CT and MRI protocol assignment quality ...

MicrographCleaner: A python package for cryo-EM micrograph cleaning using deep learning.

Cryo-EM Single Particle Analysis workflows require tens of thousands of high-quality particle projec...

Flexible Fitting of Small Molecules into Electron Microscopy Maps Using Molecular Dynamics Simulations with Neural Network Potentials.

Despite significant advances in resolution, the potential for cryo-electron microscopy (EM) to be us...

Prediction of admission in pediatric emergency department with deep neural networks and triage textual data.

Emergency department (ED) overcrowding is a global condition that severely worsens attention to pati...

Toward a unified framework for interpreting machine-learning models in neuroimaging.

Machine learning is a powerful tool for creating computational models relating brain function to beh...

Lessons Learned About Autonomous AI: Finding a Safe, Efficacious, and Ethical Path Through the Development Process.

Artificial intelligence (AI) describes systems capable of making decisions of high cognitive complex...

Effects of cost-benefit analysis under back propagation neural network on financial benefit evaluation of investment projects.

To determine the influence of the weight of the economic effectiveness evaluation criteria of the ma...

Regional Variations in Documentation of Sexual Trauma Concepts in Electronic Medical Records in the United States Veterans Health Administration.

Experiences of sexual trauma are associated with adverse patient and health system outcomes, but ar...

An AI-based approach in determining the effect of meteorological factors on incidence of malaria.

This study presents the classification of malaria-prone zones based on (a) meteorological factors, (...

The applications of machine learning in plastic and reconstructive surgery: protocol of a systematic review.

BACKGROUND: Machine learning, a subset of artificial intelligence, is a set of models and methods th...

Comparison of statistical machine learning models for rectal protocol compliance in prostate external beam radiation therapy.

PURPOSE: Limiting the dose to the rectum can be one of the most challenging aspects of creating a do...

A novel artificial intelligence protocol for finding potential inhibitors of acute myeloid leukemia.

There is currently no effective treatment for acute myeloid leukemia, and surgery is also ineffectiv...

Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project.

INTRODUCTION: Around 70% to 80% of the 19 million visually disabled children in the world are due to...

Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols.

Background Although several deep learning (DL) calcium scoring methods have achieved excellent perfo...

Short Keynote Paper: Mainstreaming Personalized Healthcare-Transforming Healthcare Through New Era of Artificial Intelligence.

Medicine has entered the digital era, driven by data from new modalities, especially genomics and im...

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis.

Understanding behavior is the first step to truly understanding neural mechanisms in the brain that ...

Towards Domain Invariant Heart Sound Abnormality Detection Using Learnable Filterbanks.

OBJECTIVE: Cardiac auscultation is the most practiced non-invasive and cost-effective procedure for ...

Determination of causes of death via spectrochemical analysis of forensic autopsies-based pulmonary edema fluid samples with deep learning algorithm.

This study investigated whether infrared spectroscopy combined with a deep learning algorithm could ...

l-l state estimation for delayed artificial neural networks under high-rate communication channels with Round-Robin protocol.

In this paper, the l-l state estimation problem is addressed for a class of delayed artificial neura...

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