Surgery

A Lung CT Foundation Model Facilitating Disease Diagnosis and Medical Imaging

The concomitant development and evolution of lung computed tomography (CT) and artificial intelligence (AI) has allowed non-invasive lung imaging to be a key part of the clinical care of patients with major diseases, such as lung cancer. However, the paucity of labeled lung CT data has limited the training highly efficacious AI models and thereby has retarded broad-scale adoption and deployment of...

ICU Readmission Prediction for Intracerebral Hemorrhage Patients using MIMIC III and MIMIC IV Databases

Intracerebral hemorrhage (ICH) is a critical form of stroke resulting from bleeding within the brain, with a mortality rate of 40-50% within a few days and significant risk of long-term disability. Despite the high incidence of ICU readmissions among ICH patients, the specific factors contributing to these readmissions remain unclear. This study utilizes MIMIC-III and MIMIC-IV databases to develop...

Machine Learning-Based Prediction of ICU Readmissions in Intracerebral Hemorrhage Patients: Insights from the MIMIC Databases

Intracerebral hemorrhage (ICH) is a life-risking condition characterized by bleeding within the brain parenchyma. ICU readmission in ICH patients is a...

A deep learning model for clinical outcome prediction using longitudinal inpatient electronic health records

Recent advances in deep learning show significant potential in analyzing continuous monitoring electronic health records (EHR) data for clinical outco...

Development and Validation of Machine Learning Models for Adverse Events after Cardiac Surgery

Early recognition of adverse events after cardiac surgery is vital for treatment. However, the widely used Society of Thoracic Surgery (STS) risk mode...

Evidence Based Gait Analysis Interpretation Tools (EB-GAIT)

Clinical gait analysis (CGA) has historically relied on clinician experience and judgment, leading to modest, stagnant, and unpredictable outcomes. Th...

An Efficient and Interpretable Foundation Model for Retinal Image Analysis in Disease Diagnosis

Artificial intelligence (AI) foundation models for colour fundus photography (CFP) have been extensively studied and demonstrated great potential for ...

Profiling and Predicting Faculty Assessment Behavior in Surgical Education

To study and profile the digital assessment behaviors of surgical faculty and residents, and to build a classifier to predict assessment completion, e...

Bridging the Anesthesia Digital Data Gap in Low-Middle-Income Countries: Computer Vision-Ready Paper Health Records

Surgical mortality is the third leading cause of death globally, with mortality rates in Africa double those of high-income countries despite patients...

Deep Learning-Driven EEG Analysis for Personalized Deep Brain Stimulation Programming in Parkinson’s Disease

Deep Brain Stimulation (DBS) is an invasive procedure used to alleviate motor symptoms in Parkinson’s Disease (PD) patients. While brain activity can ...

The Clinical Value of ChatGPT for Epilepsy Presurgical Decision Making: Systematic Evaluation on Seizure Semiology Interpretation

For patients with drug-resistant focal epilepsy (DRE), surgical resection of the epileptogenic zone (EZ) is an effective treatment to control seizures...

Variable pharmacokinetics of coagulation factor VIII in the perioperative settting complicates personalisation of treatment in patients with haemophilia A

Pharmacokinetic (PK)-guided dosing of factor concentrates in patients with haemophilia A is generally recommended for the optimisation of prophylactic...

Leveraging Large Language Models to Develop an Interpretable Prediction Model for Postpartum Hemorrhage Prior to the Onset of Labor

To evaluate whether large language models (LLMs) applied to prenatal clinical notes can predict postpartum hemorrhage (PPH) prior to the onset of labo...

Optimized Feature Selection and Advanced Machine Learning for Stroke Risk Prediction in Revascularized Coronary Artery Disease Patients

Coronary artery disease (CAD) is a leading cause of mortality, with stroke being a major complication following coronary revascularization procedures ...

Predicting in-hospital indicators from wearable-derived signals for cardiovascular and respiratory disease monitoring: an in silico study

Cardiovascular and respiratory diseases (CVRD) are the leading causes of death worldwide. The construction of health digital twins for patient monitor...

Spine age estimation using deep learning in lateral spine radiographs and DXA VFA to predict incident fracture and mortality

Spine age estimated from lateral spine radiographs and DXA vertebral fracture assessments (VFAs) could be associated with fracture and mortality risk....

An AI-driven machine learning approach identifies risk factors associated with 30-day mortality following total aortic arch replacement combined with stent elephant implantation

During emergency surgery, patients with acute type A aortic dissection (ATAAD) experience unfavorable outcomes throughout their hospital stay. The com...

Profile of deaths mentioning ischemic and hemorrhagic stroke in Brazil: a population-based machine learning analysis

Brazil has the highest stroke rates in Latin America. The aim of this study was to investigate the profile of deaths mentioning stroke in Brazil betwe...

High Sensitivity in Spontaneous Intracranial Hemorrhage Detection from Emergency Head CT Scans Using Meta-Learning Approach

Spontaneous intracranial hemorrhages have a high disease burden. Due to increasing medical imaging, new technological solutions for assisting in image...

Continuous Reaching and Grasping with a BCI Controlled Robotic Arm in Healthy and Stroke-Affected Individuals

Recent advancements in signal processing techniques have enabled non-invasive Brain-Computer Interfaces (BCIs) to control assistive devices, like robo...