Domestic Violence

Robotic esophagectomy and 3-field lymphadenectomy with intraoperative nerve monitoring.

The standard of care for esophageal malignancies has evolved over the years from open transthoracic esophagectomy to a minimally invasive approach due to the reduction in surgical trauma and significant impact on postoperative outcomes. Minimally invasive approaches include video-assisted thoracoscopic surgery and robot-assisted thoracoscopic surgery. These minimally invasive approaches have an at...

Delirium screening in an acute care setting with a machine learning classifier based on routinely collected nursing data: A model development study.

Delirium screening in acute care settings is a resource intensive process with frequent deviations from screening protocols. A predictive model relying only on daily collected nursing data for delirium screening could expand the populations covered by such screening programs. Here, we present the results of the development and validation of a series of machine-learning based delirium prediction mo...

Clustering of trauma patients based on longitudinal data and the application of machine learning to predict recovery.

Predicting recovery after trauma is important to provide patients a perspective on their estimated future health, to engage in shared decision making ...

Artificial intelligence in pancreatic cancer.

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%. The pancreatic cancer patients diagnosed with early sc...

Measuring the impact of simulation debriefing on the practices of interprofessional trauma teams using natural language processing.

BACKGROUND: Natural language processing (NLP) may be a tool for automating trauma teamwork assessment in simulated scenarios.

Prediction of Prognosis in Patients with Trauma by Using Machine Learning.

We developed a machine learning algorithm to analyze trauma-related data and predict the mortality and chronic care needs of patients with trauma. W...

Neural Networks for Survival Prediction in Medicine Using Prognostic Factors: A Review and Critical Appraisal.

Survival analysis deals with the expected duration of time until one or more events of interest occur. Time to the event of interest may be unobserved...

DENVIS: Scalable and High-Throughput Virtual Screening Using Graph Neural Networks with Atomic and Surface Protein Pocket Features.

Computational methods for virtual screening can dramatically accelerate early-stage drug discovery by identifying potential hits for a specified targe...

Development and validation of chest CT-based imaging biomarkers for early stage COVID-19 screening.

Coronavirus Disease 2019 (COVID-19) is currently a global pandemic, and early screening is one of the key factors for COVID-19 control and treatment. ...

Adverse events in the digital age and where to find them.

Exponential growth of health-related data collected by digital tools is a reality within pharmaceutical and medical device research and development. D...

Quality of reporting of randomised controlled trials of artificial intelligence in healthcare: a systematic review.

OBJECTIVES: The aim of this study was to evaluate the quality of reporting of randomised controlled trials (RCTs) of artificial intelligence (AI) in h...

Natural Language Processing in Spine Surgery: A Systematic Review of Applications, Bias, and Reporting Transparency.

BACKGROUND: Natural language processing (NLP) is a discipline of machine learning concerned with the analysis of language and text. Although NLP has b...

Improvement of intervention information detection for automated clinical literature screening during systematic review.

Systematic literature review (SLR) is a crucial method for clinicians and policymakers to make their decisions in a flood of new clinical studies. Bec...

A pilot study of deep learning-based CT volumetry for traumatic hemothorax.

PURPOSE: We employ nnU-Net, a state-of-the-art self-configuring deep learning-based semantic segmentation method for quantitative visualization of hem...

Machine learning in point-of-care automated classification of oral potentially malignant and malignant disorders: a systematic review and meta-analysis.

Machine learning (ML) algorithms are becoming increasingly pervasive in the domains of medical diagnostics and prognostication, afforded by complex de...

Biomacromolecule-Assisted Screening for Reaction Discovery and Catalyst Optimization.

Reaction discovery and catalyst screening lie at the heart of synthetic organic chemistry. While there are efforts at catalyst design using computati...

In-depth evaluation of machine learning methods for semi-automating article screening in a systematic review of mechanistic literature.

We aimed to evaluate the performance of supervised machine learning algorithms in predicting articles relevant for full-text review in a systematic re...

Drug Metabolism: A Half-Century Plus of Progress, Continued Needs, and New Opportunities.

The systematic study of drug metabolism began in the 19th Century, but most of what we know now has been learned in the last 50 years. Drug metabolism...

Detecting the sources of chemicals in the Black Sea using non-target screening and deep learning convolutional neural networks.

The Black Sea is an important ecosystem, which is affected by various anthropogenic pressures, such as shipping activities and wastewater inputs from ...

Assessment of performances of a deep learning algorithm for the detection of limbs and pelvic fractures, dislocations, focal bone lesions, and elbow effusions on trauma X-rays.

PURPOSE: To appraise the performances of an AI trained to detect and localize skeletal lesions and compare them to the routine radiological interpreta...