Refractive Surgery

Clinical Implementation of an AI Algorithm for Substance Misuse Screening in Hospitalized Adults

Manual inpatient screening for substance misuse is labor-intensive and inconsistently applied. Evaluation of artificial intelligence (AI)–assisted screening during clinical implementation is needed to determine clinical and economic performance. To assess whether an AI-based screening program with the Substance Misuse Algorithm for Referral to Treatment Using Artificial Intelligence (SMART-AI) mai...

Real-world before-and-after evaluation of AI support for lung cancer diagnosis at three US lung nodule clinics

Health systems and payers require evidence that artificial intelligence (AI)-enabled decision support improves care delivery. Integrating AI into lung nodule management pathways may streamline workflows, improve identification and triage of patients with pulmonary nodules, and enable earlier lung cancer diagnosis. Yet real-world evidence of clinical utility remains limited. This study evaluated th...

Radiologic, Pathologic, and Deep Learning Predictors of Response to Immune Checkpoint Blockade in Renal Cell Carcinoma Patients Undergoing Post-Treatment Nephrectomy

Response assessment of primary kidney tumors in the consolidation cytoreductive and neoadjuvant settings offers a unique opportunity to inform postope...

Evaluating the acceptability, usability and clinical appropriateness of Your Path, an AI-powered tool facilitating relevant access to HIV services post-HIV self-testing in South Africa

Timely linkage to HIV prevention and treatment services following HIV self-testing (HIVST) remains a challenge in many countries. While HIVST offers p...

“What witchcraft is this?”: Paramedics report gains in productivity, well-being, and patient flow from piloting ambient voice technology in an NHS Ambulance Service

UK ambulance services face record demand, resourcing challenges and rising clinical documentation burden. Ambient voice technology (AVT) coupled with ...

Machine Learning Analysis of Post-Acute COVID Symptoms Identifies Distinct Clusters, Severity Groups, and Trajectories

Questionnaires that capture patient-reported symptomatology provide low-cost but potentially high-value data for the de novo discovery of disease phen...

Machine Learning–based Prediction of LASIK Console Inputs for Aspheric Planning (Q-factor, Defocus, Astigmatism): A Translational Methods Study

Aspheric planning in laser refractive surgery remains difficult: surgeons often rely on empirical nomo-grams or simple linear regression for defocus a...

Development and evaluation of machine learning models for individualized prediction of myopia control efficacy treated with overnight orthokeratology.

PURPOSE: The primary objective of this study is to develop a predictive model utilizing fundamental clinical and ocular measurements to predict the ef...

Global trends and hotspots in artificial intelligence for high myopia: a bibliometric analysis.

PURPOSE: This study aims to conduct a bibliometric analysis of global publications on the application of artificial intelligence (AI) in high myopia (...

AntBot-EX: Enhancing robot search efficiency in complex post-disaster environments.

In post-disaster scenarios, effective rescue operations hinge on deploying robots equipped with sophisticated path planning algorithms capable of navi...

Machine learning-based infection diagnostic and prognostic models in post-acute care settings: a systematic review.

OBJECTIVES: This study aims to (1) review machine learning (ML)-based models for early infection diagnostic and prognosis prediction in post-acute car...

Leveraging artificial intelligence to promote COVID-19 appropriate behaviour in a healthcare institution from north India: A feasibility study.

Background & Objectives Non-pharmacological interventions (NPI) were crucial in curbing the initial COVID-19 pandemic waves, but compliance was diffic...

PQD: Post-training Quantization for Efficient Diffusion Models

Diffusionmodels(DMs)havedemonstratedremarkableachievements in synthesizing images of high fidelity and diversity. However, the extensive computation...

IMAGINE: An 8-to-1b 22nm FD-SOI Compute-In-Memory CNN Accelerator With an End-to-End Analog Charge-Based 0.15-8POPS/W Macro Featuring Distribution-Aware Data Reshaping

Charge-domain compute-in-memory (CIM) SRAMs have recently become an enticing compromise between computing efficiency and accuracy to process sub-8b ...

Accelerating Post-Tornado Disaster Assessment Using Advanced Deep Learning Models

Post-disaster assessments of buildings and infrastructure are crucial for both immediate recovery efforts and long-term resilience planning. This re...

Mapping the Mind of an Instruction-based Image Editing using SMILE

Despite recent advancements in Instruct-based Image Editing models for generating high-quality images, they are known as black boxes and a significa...

Precision ICU Resource Planning: A Multimodal Model for Brain Surgery Outcomes

Although advances in brain surgery techniques have led to fewer postoperative complications requiring Intensive Care Unit (ICU) monitoring, the rout...

I0T: Embedding Standardization Method Towards Zero Modality Gap

Contrastive Language-Image Pretraining (CLIP) enables zero-shot inference in downstream tasks such as image-text retrieval and classification. Howev...

Facial Surgery Preview Based on the Orthognathic Treatment Prediction

Orthognathic surgery consultation is essential to help patients understand the changes to their facial appearance after surgery. However, current vi...

Sentiment and Hashtag-aware Attentive Deep Neural Network for Multimodal Post Popularity Prediction

Social media users articulate their opinions on a broad spectrum of subjects and share their experiences through posts comprising multiple modes of ...