Ophthalmology

Refractive Surgery

Latest AI and machine learning research in refractive surgery for healthcare professionals.

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Machine learning adjusted sequential CUSUM-analyses are superior to cross-sectional analysis of excess mortality after surgery.

BACKGROUND: The assessment of clinical outcome quality, particularly in surgery, is crucial for heal...

Artificial Intelligence-Generated Writing in the ERAS Personal Statement: An Emerging Quandary for Post-graduate Medical Education.

OBJECTIVE: This study was designed to investigate if artificial intelligence (AI) detection software...

Human-Artificial Intelligence Symbiotic Reporting for Theranostic Cancer Care.

Reporting of diagnostic nuclear images in clinical cancer management is generally qualitative. Thera...

Active Machine Learning for Pre-procedural Prediction of Time-Varying Boundary Condition After Fontan Procedure Using Generative Adversarial Networks.

The Fontan procedure is the definitive palliation for pediatric patients born with single ventricles...

Post-Cardiac arrest outcome prediction using machine learning: A systematic review and meta-analysis.

BACKGROUND: Early and reliable prognostication in post-cardiac arrest patients remains challenging, ...

Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam.

Recurrent landslide events triggered by typhoons and tropical storms over Vietnam pose a longstandin...

A new approach to assess post-mortem interval: A machine learning-assisted label-free ATR-FTIR analysis of human vitreous humor.

A crucial issue in forensics is determining the post-mortem interval (PMI), the time between death a...

Effect of childhood atropine treatment on adult choroidal thickness using sequential deep learning-enabled segmentation.

PURPOSE: To describe choroidal thickness measurements using a sequential deep learning segmentation ...

A novel mean shape based post-processing method for enhancing deep learning lower-limb muscle segmentation accuracy.

This study aims at improving the lower-limb muscle segmentation accuracy of deep learning approaches...

A Lightweight Convolutional Neural Network-Reformer Model for Efficient Epileptic Seizure Detection.

A real-time and reliable automatic detection system for epileptic seizures holds significant value i...

Machine-learning-based models for the optimization of post-cervical spinal laminoplasty outpatient follow-up schedules.

BACKGROUND: Patients undergo regular clinical follow-up after laminoplasty for cervical myelopathy. ...

Machine learning for post-liver transplant survival: Bridging the gap for long-term outcomes through temporal variation features.

BACKGROUND: The long-term survival of liver transplant (LT) recipients is essential for optimizing o...

Paying attention to uncertainty: A stochastic multimodal transformers for post-traumatic stress disorder detection using video.

BACKGROUND AND OBJECTIVES: Post-traumatic stress disorder is a debilitating psychological condition ...

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