Hospitalists

Prediction of Short-Term Postoperative Complications Following Open Reduction Internal Fixation of Ankle Fractures.

BACKGROUND: Minimizing postoperative complications is imperative to improving patient outcomes. The purpose of this investigation is to develop machine learning (ML) models that can predict complications following open reduction and internal fixation of ankle fractures and compare them with legacy indices. METHODS: The ACS-NSQIP database was queried from 2011 to 2020 for ankle fractures. Training ...

An Interpretable Machine Learning Model for Early Multitemporal Prediction of Onset of Acute Kidney Injury in Intensive Care Unit Patients with Severe Trauma.

Background: Acute Kidney Injury (AKI), a leading organ failure cause in critical patients, demands early high-risk identification to enhance outcomes. Yet comparative analyses of diagnostic and prognostic machine learning (ML) models across multiple post-admission timeframes are lacking. Methods: Using MIMIC-IV, we carried out using the Boruta algorithm for feature selection, developing and compar...

Modeling homosynaptic and heterosynaptic plasticity with a single neuromemristive synapse.

INTRODUCTION: Efforts are being made to design a brain-like intelligence due to its robustness, synaptic modification (i.e., learning and memory), ana...

Artificial Intelligence in Surgery Revisited: Leveraging AI for Postoperative Instructions, Clinical Support, and Intelligent Monitoring.

Artificial intelligence (AI) is rapidly transforming surgical care, with growing integration across all phases from preoperative planning to postopera...

The Pediatric Surgeon's AI Toolbox: How Large Language Models Like ChatGPT Are Simplifying Practice and Expanding Global Access.

INTRODUCTION: Pediatric surgeons face substantial administrative workload. Large language models (LLMs) may streamline documentation, family communica...

Characterizing and predicting refractory rumination in obsessive compulsive disorder.

Rumination is problematic for individuals with obsessive compulsive disorder (OCD), and yet, is not addressed in standard treatment for OCD. Further, ...

Development of an interpretable machine learning model to predict short-term bleeding risk in patients receiving dual antithrombotic therapy following cardiac surgery.

INTRODUCTION: Bleeding is a serious complication in cardiac surgery, especially among patients receiving combined anticoagulant and antiplatelet thera...

Immune checkpoint molecules as predictive markers of COVID-19 severity: A comprehensive univariable and multivariable analysis.

Immune dysregulation plays a key role in the deterioration of COVID-19. This study evaluated immune checkpoint molecules (ICMs) as markers of disease ...

Toward Standardized ICU Trauma Resuscitation via Markov Decision Processes.

OBJECTIVE: Guideline-based recommendations for posthemostasis resuscitation in trauma patients remain limited. This study aimed to define an interpret...

Utility of Multiclass Machine Learning Algorithms in Predicting Same-Day Discharge Following Primary Total Knee Arthroplasty.

BACKGROUND: Length of stay (LOS) is a substantial driver of costs following primary total knee arthroplasty (TKA), leading to increased efforts target...

Predictive Value of Geriatric Nutritional Risk Index and Risk Analysis Index for Post-operative Outcomes in Spine Surgery Patients: A Comprehensive Analysis.

Study DesignRetrospective cohort study.ObjectivesFrailty and nutritional status are predictors of adverse spine surgery outcomes. This study evaluated...

Assessment of Multimodal Natural Language Processing in Ascertaining Perioperative Safety Indicators From Preoperative Notes in Spine Surgery.

INTRODUCTION: Standard spine surgery machine learning (ML) models often rely on structured clinical data, overlooking nuanced free text, such as preop...

Development and validation of venous thromboembolism-bidirectional encoder representations from transformers (VTE-BERT) natural language processing model.

BACKGROUND: Accurate and rapid phenotyping of venous thromboembolism (VTE) in longitudinal studies is important. A natural language processing (NLP) t...

Coronary CT angiography evaluation with artificial intelligence for individualized medical treatment of atherosclerosis: a Consensus Statement from the QCI Study Group.

Coronary CT angiography is widely implemented, with an estimated 2.2 million procedures in patients with stable chest pain every year in Europe alone....

A Dynamic Machine Learning Model to Predict Angiographic Vasospasm After Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND AND OBJECTIVES: The goal of this study was to develop a highly precise, dynamic machine learning model centered on daily transcranial Doppl...

Predictive Modeling of Comorbid Depression and Anxiety Symptoms Among Prospective University Students: A GIS-Based and Machine Learning Study.

Prospective university students are highly susceptible to mental health issues such as depression and anxiety. This study investigates the prevalence ...

AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic: Retrospective Population Cohort Study of 12,000 Patients.

BACKGROUND: One of the main challenges with COVID-19 has been that although there are known factors associated with a worse prognosis, clinicians have...

Inflammatory, fibrotic and endothelial biomarker profiles in COVID-19 patients during and following hospitalization.

Survivors of severe COVID-19 often suffer from long-term respiratory issues, but the molecular drivers of this damage remain unclear. This study explo...

Strategies to decipher neuron identity from extracellular recordings in behaving non-human primates.

Identification of neuron type is critical when using extracellular recordings in awake, behaving animal subjects to understand computation in neural c...

Machine learning approaches for predicting heart failure readmissions.

PURPOSE: This study aims to develop and evaluate machine learning (ML) models to predict the likelihood of hospital readmission within 30 days after d...