Risk Management

Intelligent, Autonomous Machines in Surgery.

Surgeons perform two primary tasks: operating and engaging patients and caregivers in shared decision-making. Human dexterity and decision-making are biologically limited. Intelligent, autonomous machines have the potential to augment or replace surgeons. Rather than regarding this possibility with denial, ire, or indifference, surgeons should understand and steer these technologies. Closer examin...

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 of structurally new chemotypes with the desired set of biological properties. Fragment-based design tools have been successfully applied in the discovery of noncovalent inhibitors. Nevertheless, these tools are rarely applied in the field of covalent inhibitor design. Herein, we present a new proto...

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 projections to unveil the three-dimensional structure of...

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 used in determining the structures of protein-drug c...

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 behavior, and its use is becoming widespread in neuro...

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 complexity; autonomous AI systems in healthcare are AI sy...

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 major investments of listed enterprises, and provide...

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 are not systematically documented in electronic heal...

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, (b) demographics and (c) patient information. Obser...

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 performance for specific CT protocols, their performanc...

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 imaging, as well as new sources such as wearables an...

Diagnosis of ventilator-associated pneumonia using electronic nose sensor array signals: solutions to improve the application of machine learning in respiratory research.

BACKGROUND: Ventilator-associated pneumonia (VAP) is a significant cause of mortality in the intensive care unit. Early diagnosis of VAP is important ...

Towards Domain Invariant Heart Sound Abnormality Detection Using Learnable Filterbanks.

OBJECTIVE: Cardiac auscultation is the most practiced non-invasive and cost-effective procedure for the early diagnosis of heart diseases. While machi...

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 neural networks under high-rate communication channels ...

Investigating the use of data-driven artificial intelligence in computerised decision support systems for health and social care: A systematic review.

There is growing interest in the potential of artificial intelligence to support decision-making in health and social care settings. There is, however...

Machine Learning Approach for Fluconazole Resistance Detection Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry.

causes life-threatening systemic infections in immunosuppressed patients. These infections are commonly treated with fluconazole, an antifungal agent...

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment.

Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its early detection is crucial in our aging societies. Com...

Biomimetic smoking robot for in vitro inhalation exposure compatible with microfluidic organ chips.

Exposure of lung tissues to cigarette smoke is a major cause of human disease and death worldwide. Unfortunately, adequate model systems that can reli...

Intracatheter Tissue Plasminogen Activator for Chronic Subdural Hematomas after Failed Bedside Twist Drill Craniostomy: A Retrospective Review.

Introduction Chronic subdural hematomas (cSDH) are common in neurosurgery with various symptoms and significant morbidity and mortality. Treatment var...

Fully automatic estimation of pelvic sagittal inclination from anterior-posterior radiography image using deep learning framework.

BACKGROUND AND OBJECTIVE: Malposition of the acetabular component causes dislocation and prosthetic impingement after Total Hip Arthroplasty (THA), wh...