Surgery

Risk assessment in cardiac surgery: Exploring machine learning and laboratory indices as adjunctive tools

Post-operative outcomes of cardiovascular surgery vary greatly among patients for a variety of reasons. While the specific reasons are often multifactorial and complex, certain machine learning methods are promising ways to both estimate mortality after surgery and elucidate important factors linked with mortality. Using the MIMIC-IV database, we identified 11,261 patients on the cardiovascular su...

Decentralized, privacy-preserving surgical video analysis with Swarm Learning

Progress in artificial intelligence-based analysis of surgical videos has been constrained by reliance on manual frame-level annotations rather than patient-level outcomes. In addition, concerns about data privacy restrict the exchange of laparoscopic video data and, thereby, multicenter collaboration. To address these limitations, we developed a pipeline that integrates weakly supervised deep lea...

The Cognitive Safety Net: Comparing Human and AI Diagnostic Reasoning during Complex Clinical Situations

Diagnostic error in high-stakes clinical environments remains a significant cause of preventable harm. While a new generation of customisable digital ...

Probing the Surgical Competence of LLMs: A global health study leveraging AfriMedQA benchmarks

Global surgical care faces a severe workforce shortage, with more than 1.2 million additional specialists needed by 2030, particularly in low- and mid...

The Seizure Embedding Map: A Spatio-Temporal Transformer for Comparing Patients by Ictal Intracranial EEG Features at Scale

Planning invasive treatment for medication-resistant epilepsy relies on qualitatively interpreting seizure recordings from intracranial EEG (iEEG) rec...

Intraoperative Metabolomic-Guided Precision Surgery for Pediatric Brain Tumors: A Systematic Review of Multi-Modal Molecular Imaging Platforms and Artificial Intelligence Integration

Pediatric brain tumors are the leading cause of cancer death in children, with surgical resection critical for survival and neurodevelopment. Intraope...

Autonomous conversational agents for loneliness, social isolation, depression and anxiety in older people without cognitive impairment: Systematic review and meta-analysis

Loneliness is a major psychological challenge in older adulthood, contributing to increased risks of depression, anxiety, and mortality. Conversationa...

Multi-branch convolutional neural network using intracranial EEG high frequency oscillation features for predicting post-surgical seizure outcomes

Pathological high-frequency oscillations (HFOs 80-600 Hz) in intracranial EEG distinguish epileptogenic cortex. However, it is uncertain whether utili...

Hemi-brain growth as a biomarker for whole brain growth

Accurate cerebrospinal fluid (CSF) and brain volume estimation are important components for evaluating hydrocephalus treatments, including shunts and ...

Prediction of Pulmonary Vein Isolation and Gap Recurrence on 12-Lead ECG Using Deep Learning

Pulmonary vein isolation (PVI) is key to atrial fibrillation (AF) ablation, but arrhythmia often recurs due to conduction gaps permitting pulmonary ve...

Evaluating Conversational Image Segmentation for Medicine: Performance, Failure Modes, and a Fairness Audit Across Seven Modalities

Medical-image segmentation underpins quantitative diagnostics and research, yet state-of-the-art models remain task-specific and data-hungry. The rece...

Automated Video-Based Analysis of Surgical Meta-competencies Using Computer Vision

Traditional surgical training relies on an apprenticeship model, which is subjective and threatened by human bias. Performance metric scales attempt t...

Artificial Intelligence Predicts Health-Related Quality of Life for Adolescent Idiopathic Scoliosis

Adolescent idiopathic scoliosis (AIS) has a large impact on health-related quality of life (HRQoL) including poor psychosocial functioning, body image...

Improving Doctor-Patient Communication Using Large Language Models - Results from an Experimental Study

Medical jargon poses significant barriers to patient comprehension of healthcare information, potentially affecting treatment adherence and health out...

Employing Consensus-Based Reasoning with Locally Deployed LLMs for Enabling Structured Data Extraction from Surgical Pathology Reports

Surgical pathology reports provide essential diagnostic information critical for cancer staging, treatment planning, and cancer registry documentation...

The impact of a SmartPhone applicatiOn for skin cancer risk assessmenT on the healthcare system (SPOT-study): A randomized controlled trial

Artificial intelligence (AI)-based mobile health (mHealth) smartphone apps for skin cancer detection are increasingly available to the general populat...

Prediction of TP53 biomarkers and survival outcomes from whole slide images using a vision transformer-based multi-instance learning framework

Accurate molecular profiling and prognostication from routine histopathology slides could transform precision oncology. We developed a Vision Transfor...

Continuous Multimodal AI with Wearable Vital Signs Predicts Postoperative Complications in the General Ward

Surgery is inherently associated with complications, making early detection the cornerstone of timely intervention and improved outcomes. Artificial i...

Intraoperative classification of glioblastoma through near real-time stimulated Raman scattering microscopy

Glioblastoma is a highly malignant brain tumor in which maximal safe resection is associated with improved survival, yet the oncological benefit of re...

Machine learning model predicts new-onset lower extremity deep vein thrombosis after pelvic fracture surgery and targeted diagnosis

Postoperative new-onset deep vein thrombosis (PNO-DVT) of the lower extremities represents a prevalent and serious clinical complication following pel...