Ophthalmology

Exploring AI Driven Autonomous Vehicles as Mobile Health Units to Expand Access to Healthcare in Underserved Communities.

Access to quality healthcare remains a persistent challenge in many low- and middle-income countries, especially for rural and underserved populations. This paper explores the transformative potential of autonomous vehicles (AVs) as mobile health units, proposing a new model for healthcare delivery that leverages emerging transportation technology. We examine how AVs can be equipped with diagnosti...

Advancing workpiece dimension measurement: Integrating AI-based edge detection with machine vision and coordinate measuring systems.

Image preprocessing and edge detection are critical in industrial machine vision for workpiece dimension measurement. Challenges arise from interference regions on workpiece surfaces, complicating edge detection and roundness assessment. This paper investigates the application of AI-based detection methods within the industrial image analysis framework of coordinate measuring machines. Initially, ...

Impact of Computer-Aided Detection on Endoscopist's Gaze-Shift Distance During Colonoscopy: a Randomized Controlled Trial (With Video).

BACKGROUND AND AIM: Computer-aided detection (CADe) facilitates colorectal lesion detection, but it remains unclear whether CADe affects endoscopist's...

Comprehensive Evaluation of ChatGPT's Diagnostic Accuracy on Image-based Ophthalmic Case Interpretations.

OBJECTIVE: To evaluate the diagnostic and treatment accuracy of Chat Generative Pre-trained Transformer (GPT-4.o) in ophthalmology, comparing performa...

A Novel Quantitative Analysis in Myocardial Perfusion Imaging: How does it compare to the "Golden Eye"?

Myocardial Perfusion Imaging is widely used to evaluate left ventricular perfusion in patients with ischemic heart disease. Semi-quantitative scores, ...

Interpretable machine learning reveals metabolomic signatures: biomarkers and mechanisms in acute vs chronic angle-closure glaucoma.

CorvisST biomechanical indices in the diagnosis of corneal stromal and endothelial disorders: an artificial intelligence-based comparative study.

AIMS: To analyse the value of the CorvisST indices in diagnosing corneal stromal and endothelial disorders (CSEDs). METHODS: This institutional retros...

3D human pose keypoints and corresponding joint angle calculation for vision-based WMSD risk assessments.

Vision-based pose estimation, which can utilise ordinary videos, has been applied to assess work-related musculoskeletal disorder (WMSD) risks as a le...

Fuzzy logic for preanesthetic risk assessment in cataract surgery patients.

We aimed to build a fuzzy logic preanaesthetic risk score tailored to cataract surgery. By fusing systemic comorbidities with key patient attributes i...

Comparing the Accuracy of 4 Artificial Intelligence Models in PubMed Citation Generation for Glaucoma Research.

PRCIS: DeepSeek, a biomedically enriched AI model, achieved the highest accuracy in generating PubMed citations for glaucoma research, outperforming g...

Coaxial Hydrogel Optical Fibre Skin for Interference-Free Multimodal Tactile Perception.

Flexible photonic fibers enable precise, interference-free multimodal tactile sensing in wearable interfaces, owing to their intrinsic immunity to ele...

Expression of Concern: Enhanced surface plasmon resonance biosensor with graphene-black phosphorus heterostructure for ultra-high sensitivity refractive index detection with machine learning for behaviour prediction.

Effects of physically embodied educational robots on children's learning outcomes: A meta-analysis.

Physically embodied educational robots (PERs) are increasingly integrated into classrooms, yet evidence on their impact on children's learning remains...

Effects of climate and air pollution on rates of hospitalization for affective mood disorders in southern Brazil.

Climate change and air pollution are two of the most pressing global challenges, increasingly recognized for their implications on health. Thus, we ai...

Development and Validation of Machine Learning Model to Predict Refractory Septic Shock.

This study developed and validated a machine learning model to predict refractory septic shock in patients with sepsis admitted to a tertiary care cen...

A framework of hybrid deep learning and nature-inspired algorithms for accurate multi-class fundus disease classification.

Fundus imaging is an essential technique for detecting anatomical changes indicative of various ophthalmological diseases. These alterations-including...

'Bad manners'-refocusing on 'bedside manner' as a core professional behaviour for doctors.

Healthcare systems globally face unprecedented pressures, with increasing patient volumes and resource constraints affecting care delivery. While syst...

Integrated Radiomics-Enhanced machine learning models for accurate diagnosis and prediction of oGVHD-Related ocular complications.

Identity interweaving, act boundaries, illusion and reality interweaving: A study of visual narratives of scientists and citizen scientists through AI.

The rise of generative artificial intelligence (AI) is transforming human-computer interaction, reshaping communication methods and altering public pe...

Integrated molecular and clinical profiling of primary mitochondrial oxidative phosphorylation disorders in an Indian cohort: Insights from genetics, neuroimaging, and machine learning.

Primary mitochondrial disorders are clinically and genetically heterogeneous and remain underdiagnosed in resource-limited settings. We performed a re...