Refractive Surgery

Artificial Intelligence-Based Algorithms Improve Care of Patients with AAA.

BACKGROUND: Timely detection and monitoring of abdominal aortic aneurysms (AAAs) are necessary to prevent ruptures and decrease mortality. Artificial intelligence (AI)-based algorithms can automatically detect the presence of AAA on imaging and radiology reports. The goal of this study is to examine the impact of AI utilization on AAA detection and care while comparing it to historical standard of...

'Brain + X': Interdisciplinary health professions education for the AI era.

Artificial intelligence (AI) is reshaping healthcare, necessitating a transformation in health professions education. To prepare future professionals for an AI-integrated landscape, curricula must evolve beyond traditional biomedical training to incorporate interdisciplinary knowledge and AI-related competencies. However, current education often falls short in equipping students with the necessary...

Advancements in ocular blood flow imaging: Clinical applications of laser speckle flowgraphy and optical coherence tomography angiography in retinal and choroidal vascular diseases.

Ocular blood flow imaging techniques have become indispensable in current clinical practice because retinal vascular disturbances have been implicated...

Nivolumab plus ipilimumab for potentially resectable hepatocellular carcinoma: Long-term efficacy and biomarker exploration.

BACKGROUND & AIMS: Immune checkpoint inhibitor-based combination therapy has demonstrated high objective response rates in patients with hepatocellula...

A Causal Machine Learning Framework for Estimating the Impact of Cancer Diagnosis on Receipt of Advance Care Planning.

OBJECTIVE: Develop a causal machine learning (causal ML) framework for estimating how a diagnosis (cancer in this study) affects the likelihood of rec...

Dissecting the clinical and pathophysiological complexity of fundus tessellation.

Fundus tessellation (FT)-also referred to as tigroid or mosaic fundus-is characterized by increased visibility of underlying choroidal vessels. While ...

Fusion of Deep Transfer Learning and Radiomics in MRI-Based Prediction of Post-Surgical Recurrence in Soft Tissue Sarcoma.

Soft  tissue sarcomas (STS) are heterogeneous malignancies with high recurrence rates (33-39%) post-surgery, necessitating improved prognostic tools. ...

Predictive Value of Geriatric Nutritional Risk Index and Risk Analysis Index for Post-operative Outcomes in Spine Surgery Patients: A Comprehensive Analysis.

Study DesignRetrospective cohort study.ObjectivesFrailty and nutritional status are predictors of adverse spine surgery outcomes. This study evaluated...

Unsupervised machine learning to explore inflammation following cardiopulmonary bypass.

IntroductionCardiac surgery with cardiopulmonary bypass (CPB) often induces systemic inflammatory reaction syndrome (SIRS), affecting postoperative ou...

Ultra-Low-Dose CTPA Using Sparse Sampling CT Combined with the U-Net for Deep Learning-Based Artifact Reduction: An Exploratory Study.

This retrospective study evaluates U-Net-based artifact reduction for dose-reduced sparse-sampling CT (SpSCT) in terms of image quality and diagnostic...

Machine learning models to predict postoperative incontinence after endoscopic enucleation of the prostate for benign prostatic hyperplasia: An EAU-Endourology study.

BACKGROUND: Machine learning (ML) and artificial intelligence (AI) have demonstrated powerful functionality in the healthcare setting thus far. We aim...

Detecting Artificial Intelligence-Generated Text in Personal Statements of Adult Reconstruction Fellowship Applicants.

BACKGROUND: Artificial intelligence (AI), particularly large language models such as Chat Generative Pre-Trained Transformer (ChatGPT), has expanded a...

Evaluating Dynamic Smile Outcomes of Free Gracilis Muscle Transfer in Pediatric Facial Palsy Using Image-Based Analysis.

BACKGROUND: Facial nerve palsy in children leads to significant functional impairment and facial asymmetry. While free gracilis muscle transfer (FGMT)...

Artificial intelligence-based action recognition and skill assessment in robotic cardiac surgery simulation: a feasibility study.

To create a deep neural network capable of recognizing basic surgical actions and categorizing surgeons based on their skills using video data only. N...

Diagnosing pathologic myopia by identifying morphologic patterns using ultra widefield images with deep learning.

Pathologic myopia is a leading cause of visual impairment and blindness. While deep learning-based approaches aid in recognizing pathologic myopia usi...

Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery.

While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, ...

Deep learning for predicting myopia severity classification method.

BACKGROUND: Myopia is a major cause of vision impairment. To improve the efficiency of myopia screening, this paper proposes a deep learning model, X-...

Post-hoc eXplainable AI methods for analyzing medical images of gliomas (- A review for clinical applications).

Deep learning (DL) has shown promise in glioma imaging tasks using magnetic resonance imaging (MRI) and histopathology images, yet their complexity de...

Exploratory development of human-machine interaction strategies for post-stroke upper-limb rehabilitation.

BACKGROUND: Stroke and its related complications, place significant burdens on human society in the twenty-first century, and lead to substantial dema...

Beyond Recanalization: Machine Learning-Based Insights into Post-Thrombectomy Vascular Morphology in Stroke Patients.

Many stroke patients have poor outcomes despite successful endovascular therapy (EVT). We hypothesized that machine learning (ML)-based analysis of va...