Risk Management

Physics-based protein structure refinement in the era of artificial intelligence.

Protein structure refinement is the last step in protein structure prediction pipelines. Physics-based refinement via molecular dynamics (MD) simulations has made significant progress during recent years. During CASP14, we tested a new refinement protocol based on an improved sampling strategy via MD simulations. MD simulations were carried out at an elevated temperature (360 K). An optimized use ...

Equivalent-input-disturbance estimator-based event-triggered control design for master-slave neural networks.

This paper investigates the robust synchronization problem for a class of master-slave neural networks (MSNNs) subject to network-induced delays, unknown time-varying uncertainty, and exogenous disturbances. An equivalent-input-disturbance (EID) estimation technique is applied to compensate for the effects of unknown uncertainty and disturbances in the system output. In addition, to reduce the bur...

Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol.

INTRODUCTION: Standards for Reporting of Diagnostic Accuracy Study (STARD) was developed to improve the completeness and transparency of reporting in ...

Deepometry, a framework for applying supervised and weakly supervised deep learning to imaging cytometry.

Deep learning offers the potential to extract more than meets the eye from images captured by imaging flow cytometry. This protocol describes the appl...

A Multifunctional Smart Meter Using ANN-PSO Flux Estimation and Harmonic Active Compensation with Fuzzy Voltage Regulation.

This paper aims to present the analysis and development of a complete electronic smart meter that is able to perform four-quadrant measurements, act a...

Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration.

OBJECTIVES: To evaluate the image quality and iodine concentration (IC) measurements in pancreatic protocol dual-energy computed tomography (DECT) rec...

Optimizing Robotic Hysterectomy for the Patient Who Is Morbidly Obese with a Surgical Safety Pathway.

STUDY OBJECTIVE: Obesity is a growing worldwide epidemic, and patients classified as obese undergoing gynecologic robotic surgery are at increased ris...

The need to separate the wheat from the chaff in medical informatics: Introducing a comprehensive checklist for the (self)-assessment of medical AI studies.

This editorial aims to contribute to the current debate about the quality of studies that apply machine learning (ML) methodologies to medical data to...

Pseudo-pneumatosis of the gastrointestinal tract: its incidence and the accuracy of a checklist supported by artificial intelligence (AI) techniques to reduce the misinterpretation of pneumatosis.

PURPOSE: To assess the incidence of erroneous diagnosis of pneumatosis (pseudo-pneumatosis) in patients who underwent an emergency abdominal CT and to...

Ligand-Dependent Conformational Transitions in Molecular Dynamics Trajectories of GPCRs Revealed by a New Machine Learning Rare Event Detection Protocol.

Central among the tools and approaches used for ligand discovery and design are Molecular Dynamics (MD) simulations, which follow the dynamic changes ...

Machine learning in medicine: should the pursuit of enhanced interpretability be abandoned?

We argue why interpretability should have primacy alongside empiricism for several reasons: first, if machine learning (ML) models are beginning to re...

Presenting artificial intelligence, deep learning, and machine learning studies to clinicians and healthcare stakeholders: an introductory reference with a guideline and a Clinical AI Research (CAIR) checklist proposal.

Background and purpose - Artificial intelligence (AI), deep learning (DL), and machine learning (ML) have become common research fields in orthopedics...

Thoracic Point-of-Care Ultrasound: A SARS-CoV-2 Data Repository for Future Artificial Intelligence and Machine Learning.

Current experience suggests that artificial intelligence (AI) and machine learning (ML) may be useful in the management of hospitalized patients, incl...

Conjunctival Provocation Test With .

Conjunctival provocation test (CPT) is used to demonstrate clinical relevance to a specific allergen. (Bt) is a prevalent allergen in tropical regio...

Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records.

Early prediction of patient outcomes is important for targeting preventive care. This protocol describes a practical workflow for developing deep-lear...

Q-CHAT-NAO: A robotic approach to autism screening in toddlers.

The use of humanoid robots as assistants in therapy processes is not new. Several projects in the past several years have achieved promising results w...

Computational generation of proteins with predetermined three-dimensional shapes using ProteinSolver.

Computational generation of new proteins with a predetermined three-dimensional shape and computational optimization of existing proteins while mainta...

Clinical applications of AI in MSK imaging: a liability perspective.

Artificial intelligence (AI) applications have been gaining traction across the radiology space, promising to redefine its workflow and delivery. Howe...

Quantitative salivary gland SPECT/CT using deep convolutional neural networks.

Quantitative single-photon emission computed tomography/computed tomography (SPECT/CT) using Tc-99m pertechnetate aids in evaluating salivary gland fu...

Artefact Detection in Impedance Pneumography Signals: A Machine Learning Approach.

Impedance pneumography has been suggested as an ambulatory technique for the monitoring of respiratory diseases. However, its ambulatory nature makes ...