Hospitalists

CFD-driven neural network and SVM models for airfoil aerodynamic enhancement with bio-inspired riblets and plasma actuation.

Enhancing the airfoil performance using advanced flow control techniques is an important challenge in the aerospace and automotive industries. In this article a hybrid computational and artificial intelligence (AI) approach is developed for aerodynamic performance enhancement of a NACA4412 airfoil by using a combination of bio inspired riblets and active plasma control. Semi circular, triangular a...

ChatGPT in liver transplantation: Current applications, limitations, and future directions.

Liver transplantation (LT) remains the optimal life-saving intervention for patients with end-stage liver disease. Despite the recent advances in LT several barriers, including organ allocation, donor-recipient matching, and patient education, persist. With the growing progress of artificial intelligence, particularly large language models (LLMs) like ChatGPT, new applications have emerged in the ...

Development and Validation of a Machine Learning-Based Nomogram for Predicting Severe Pneumocystis jirovecii Pneumonia in Kidney Transplant Recipients.

BACKGROUND Pneumocystis jirovecii pneumonia (PJP) is a life-threatening opportunistic infection in kidney transplant recipients (KTRs). Early identifi...

Explainable machine learning for postoperative respiratory failure prediction in open-heart surgery patients - a study based on the MIMIC-IV database.

BACKGROUND: Postoperative respiratory failure (PRF) is a severe complication after open-heart surgery, associated with increased mortality and prolong...

Evaluating the Performance of Large Language Models for Generating Emergency Department Discharge Instructions.

BACKGROUND: Clear discharge instructions are essential for safe emergency department (ED) care, yet creating patient-centered, health literate materia...

Predicting infarct outcomes after extended time window thrombectomy in large vessel occlusion using knowledge guided deep learning.

BACKGROUND: Predicting the final infarct after an extended time window mechanical thrombectomy (MT) is beneficial for treatment planning in acute isch...

Automated auditing of emergency department documentation using large language models.

INTRODUCTION: Errors in emergency department (ED) documentation can lead to patient harm and medicolegal risk, however manual document auditing is res...

Informatics for Infection Prevention and Control.

Computer informatics is integral to infection control, a role that will grow as surveillance and reporting become increasingly automated. Surveillance...

Construction and validation of a predictive model for suicidal attempts in patients with mood disorders after discharge based on machine learning methods: A two-year follow-up study.

BACKGROUND: Suicide attempts (SA) in patients with mood disorders (MD) should be paid enough attention. Currently, there is a lack of relevant researc...

Self-Powered Multisensor with Electromagnetic and Triboelectric Energy Harvesting for Wireless Monitoring in Every Knee Joint Motion.

Artificial Intelligence of Things (AIoT) enables convenient human health monitoring but consumes massive data and energy. Traditional power supplies a...

Machine Learning in Discharge Planning for Stroke Patients: A Review of Feature Representation and Aggregation Strategies With Suggestions for Improvement.

Association between stress hyperglycemia ratio and all-cause mortality in neurocritical patients.

Fluctuations in blood glucose during acute neurocritical illness are associated with poor outcomes, but the role of stress hyperglycemia ratio (SHR) i...

Identifying patients at risk for short-term adverse events after hip arthroscopy: a machine learning analysis of a national database.

PURPOSE: To develop and compare machine learning-based risk prediction models to identify patients at risk for short-term adverse outcomes (overnight ...

Natural Language Processing and Machine Learning Classification Model for Injury Mechanism in Trauma.

INTRODUCTION: Creating and maintaining research databases in trauma can be resource intensive. Natural language processing (NLP) may assist by extract...

In situ trophic modes and metabolic traits of the dinoflagellate Karenia in response to short-term localized warming.

Algae primarily rely on photosynthesis, but many taxa can adopt mixotrophic strategies that integrate photoautotrophic and phago-heterotrophic nutriti...

Fundamental understanding of electrochemical energy storage devices via in situ or operando characterization.

The importance of mechanistic studies in the field of energy storage cannot be understated. Electrochemical characterization alone cannot provide a co...

Using Machine Learning to Predict Features Within Substance Use Disorder Treatment Service Settings That Increase the Likelihood of Positive Treatment Outcomes.

Given the conceptual issues involved in defining and measuring recovery and accordingly substance use disorder (SUD) treatment outcomes, the role of e...

Collaborative Coarse-to-Fine Disease Learning With Discharge Summary Awareness for EHR Event Prediction.

Deep learning-based models have been widely used to predict electronic health record (EHR) events by exploiting diagnostic characteristics. Despite si...

A novel stacking ensemble model for predicting discharge coefficient of submerged multi parallel radial gates.

Multimodal AI-based 28-day mortality prediction of pneumonia patients at ED discharge: a multicenter study.