Emergency Medicine

Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning.

Although the prevalence of autism spectrum disorder (ASD) has risen sharply in the last few years reaching 1 in 68, the average age of diagnosis in the United States remains close to 4--well past the developmental window when early intervention has the largest gains. This emphasizes the importance of developing accurate methods to detect risk faster than the current standards of care. In the prese...

Surgical robots for SPL and NOTES: a review.

INTRODUCTION: Single port laparoscopy (SPL) and natural orifice transluminal endoscopic surgery (NOTES) are next-generation minimally invasive surgery (MIS) procedures which could further reduce patient trauma. Robotic assistance shows great potential in providing augmented motion precision and manipulation dexterity. This article reviews the robotic systems recently developed for SPL and NOTES.

Robotic natural orifice transluminal endoscopic surgery (R-NOTES): literature review and prototype system.

In minimally invasive surgery methods such as laparoscopic surgery, surgical instruments are introduced through small incisions to minimize patient tr...

Bayesian models trained with HTS data for predicting β-haematin inhibition and in vitro antimalarial activity.

A large quantity of high throughput screening (HTS) data for antimalarial activity has become available in recent years. This includes both phenotypic...

Robotic telepresence versus standardly supervised stroke alert team assessments.

BACKGROUND: Telemedicine has created access to emergency stroke care for patients in all communities, regardless of geography. We hypothesized that th...

Quantitative analysis of mitochondrial morphology and membrane potential in living cells using high-content imaging, machine learning, and morphological binning.

Understanding the processes of mitochondrial dynamics (fission, fusion, biogenesis, and mitophagy) has been hampered by the lack of automated, determi...

ADReCS: an ontology database for aiding standardization and hierarchical classification of adverse drug reaction terms.

Adverse drug reactions (ADRs) are noxious and unexpected effects during normal drug therapy. They have caused significant clinical burden and been res...

Modeling analgesic drug interactions using support vector regression: a new approach to isobolographic analysis.

BACKGROUND: Modeling drug interactions is important for illustrating combined drug actions and for predicting the pharmacological and/or toxicological...

Automated clinical trial eligibility prescreening: increasing the efficiency of patient identification for clinical trials in the emergency department.

OBJECTIVES: (1) To develop an automated eligibility screening (ES) approach for clinical trials in an urban tertiary care pediatric emergency departme...

Artificial neural networks in neurosurgery.

Artificial neural networks (ANNs) effectively analyze non-linear data sets. The aimed was A review of the relevant published articles that focused on ...

Machine learning-based augmented reality for improved surgical scene understanding.

In orthopedic and trauma surgery, AR technology can support surgeons in the challenging task of understanding the spatial relationships between the an...

Estimation of optimal pivot point for remote center of motion alignment in surgery.

PURPOSE: The determination of an optimal pivot point ([Formula: see text]) is important for instrument manipulation in minimally invasive surgery. Suc...

AI-Enabled Echocardiography Identifies an Adverse Epicardial Adiposity Phenotype Associated with Cardiometabolic Dysfunction

Background: Excess epicardial adipose tissue (EAT) is associated with cardiovascular-kidney-metabolic (CKM) dysfunction, but its assessment has tradit...

FSB-Net: Frequency-Spatial Boundary Network for Brain Stroke Lesion Segmentation in Non-Contrast CT

Accurate segmentation of brain stroke lesions in non-contrast computed tomography (NCCT) scans is critical for rapid clinical decision-making, yet rem...

PRISM-DR: Per-lesion Retinal Inference with Specialist Models for Diabetic Retinopathy

Diabetic retinopathy is a leading cause of preventable blindness; its early lesions are small, low contrast, and easily missed in manual screening. Mo...

Harnessing Disagreement: Detecting Correlated Agreement Blindness in Multi-Agent Triage

Disagreement-triggered escalation can create a structural blind spot in multi-agent arbitration: as base learners improve, they tend to converge, weak...

From CHESS to CHECKMATE: A Practical Score for Predicting Shunt Dependency Following Subarachnoid Hemorrhage

Objective: Shunt-dependent hydrocephalus is a common and costly complication of aneurysmal subarachnoid hemorrhage (aSAH), affecting up to 28% of surv...

Multi-model Segmentation and Morphometric Quantification of Cerebral Amyloid Angiopathy in Alzheimer's Disease Whole Slide Histopathology Images

Introduction: Cerebral amyloid angiopathy (CAA) is characterized by amyloid-beta deposition in cortical and leptomeningeal vessels and associated with...

Image Editing Models are Numerical Solvers

We investigate whether a pretrained generative image-editing model can provide a common interface for numerical simulation. Physical inputs and soluti...

Biological Amnesia in ICU Time-Series Prediction: A Drift-Adaptive Two-Stream Architecture with Temporal Retrieval

Background: Clinical decision support systems degrade silently as treatment protocols evolve, yet standard adaptation methods treat models as monolith...