Refractive Surgery

Diagnosis of Pulmonary Hypertension by Integrating Multimodal Data with a Hybrid Graph Convolutional and Transformer Network

Early and accurate diagnosis of pulmonary hypertension (PH) is essential for optimal patient management. Differentiating between pre-capillary and post-capillary PH is critical for guiding treatment decisions. This study develops and validates a deep learning-based diagnostic model for PH, designed to classify patients as non-PH, pre-capillary PH, or post-capillary PH. This retrospective study a...

Post-Incorporating Code Structural Knowledge into LLMs via In-Context Learning for Code Translation

Code translation migrates codebases across programming languages. Recently, large language models (LLMs) have achieved significant advancements in software mining. However, handling the syntactic structure of source code remains a challenge. Classic syntax-aware methods depend on intricate model architectures and loss functions, rendering their integration into LLM training resource-intensive. T...

3D Structural Phenotype of the Optic Nerve Head at the Intersection of Glaucoma and Myopia -- A Key to Improving Glaucoma Diagnosis in Myopic Populations

Purpose: To characterize the 3D structural phenotypes of the optic nerve head (ONH) in patients with glaucoma, high myopia, and concurrent high myop...

Improving Quantization with Post-Training Model Expansion

The size of a model has been a strong predictor of its quality, as well as its cost. As such, the trade-off between model cost and quality has been ...

Post-composing ontology terms for efficient phenotyping in plant breeding.

Ontologies are widely used in databases to standardize data, improving data quality, integration, and ease of comparison. Within ontologies tailored t...

Mapping intellectual structure and research hotspots of cancer studies in primary health care: A machine-learning-based analysis.

In the contemporary fight against cancer, primary health care (PHC) services hold a significant and critical position within the healthcare system. Th...

Coupling deep and handcrafted features to assess smile genuineness

Assessing smile genuineness from video sequences is a vital topic concerned with recognizing facial expression and linking them with the underlying ...

[Application Practice of AI Empowering Post-discharge Specialized Disease Management in Postoperative Rehabilitation of the Lung Cancer Patients Undergoing Surgery].

BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widesprea...

SMILE: a Scale-aware Multiple Instance Learning Method for Multicenter STAS Lung Cancer Histopathology Diagnosis

Spread through air spaces (STAS) represents a newly identified aggressive pattern in lung cancer, which is known to be associated with adverse progn...

Combined impact of grey and superficial white matter abnormalities: implications for epilepsy surgery

Drug-resistant focal epilepsy is associated with abnormalities in the brain in both grey matter (GM) and superficial white matter (SWM). However, it...

ACT360: An Efficient 360-Degree Action Detection and Summarization Framework for Mission-Critical Training and Debriefing

Effective training and debriefing are critical in high-stakes, mission-critical environments such as disaster response, military simulations, and in...

Developing and Evaluating an AI-Assisted Prediction Model for Unplanned Intensive Care Admissions following Elective Neurosurgery using Natural Language Processing within an Electronic Healthcare Record System

Introduction: Timely care in a specialised neuro-intensive therapy unit (ITU) reduces mortality and hospital stays, with planned admissions being sa...

A Novel Ophthalmic Benchmark for Evaluating Multimodal Large Language Models with Fundus Photographs and OCT Images

In recent years, large language models (LLMs) have demonstrated remarkable potential across various medical applications. Building on this foundatio...

Periodontal Bone Loss Analysis via Keypoint Detection With Heuristic Post-Processing

Calculating percentage bone loss is a critical test for periodontal disease staging but is sometimes imprecise and time consuming when manually calc...

SePer: Measure Retrieval Utility Through The Lens Of Semantic Perplexity Reduction

Large Language Models (LLMs) have demonstrated improved generation performance by incorporating externally retrieved knowledge, a process known as r...

PEO: Improving Bi-Factorial Preference Alignment with Post-Training Policy Extrapolation

The alignment of large language models with human values presents a critical challenge, particularly when balancing conflicting objectives like help...

Feasibility of a Machine Learning Classifier for Predicting Post-Induction Hypotension in Non-Cardiac Surgery.

PURPOSE: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries.

Automatic Temporal Segmentation for Post-Stroke Rehabilitation: A Keypoint Detection and Temporal Segmentation Approach for Small Datasets

Rehabilitation is essential and critical for post-stroke patients, addressing both physical and cognitive aspects. Stroke predominantly affects olde...

Clinical Inspired MRI Lesion Segmentation

Magnetic resonance imaging (MRI) is a potent diagnostic tool for detecting pathological tissues in various diseases. Different MRI sequences have di...

PQBFL: A Post-Quantum Blockchain-based Protocol for Federated Learning

One of the goals of Federated Learning (FL) is to collaboratively train a global model using local models from remote participants. However, the FL ...