Ophthalmology

LDMRes-Net: A Lightweight Neural Network for Efficient Medical Image Segmentation on IoT and Edge Devices.

In this study, we propose LDMRes-Net, a lightweight dual-multiscale residual block-based convolutional neural network tailored for medical image segmentation on IoT and edge platforms. Conventional U-Net-based models face challenges in meeting the speed and efficiency demands of real-time clinical applications, such as disease monitoring, radiation therapy, and image-guided surgery. In this study,...

Prognosis Prediction of Diffuse Large B-Cell Lymphoma in F-FDG PET Images Based on Multi-Deep-Learning Models.

Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and complicated diseases because of its considerable variation in clinical behavior, response to therapy, and prognosis. Radiomic features from medical images, such as PET images, have become one of the most valuable features for disease classification or prognosis prediction using learning-based metho...

Using Pupil Diameter for Psychological Resilience Assessment in Medical Students Based on SVM and SHAP Model.

Effectively assessing psychological resilience for medical students is vital for identifying at-risk individuals and developing tailored interventions...

Artificial Intelligence-Based Ocular Motor Biomarkers for Myasthenia Gravis Diagnosis (P10-11.016).

Fully Automatic Deep Learning Model for Spine Refracture in Patients with OVCF: A Multi-Center Study.

BACKGROUND: The reaserch of artificial intelligence (AI) model for predicting spinal refracture is limited to bone mineral density, X-ray and some con...

Algorithmic bias: Social science research integration through the 3-D Dependable AI Framework.

Algorithmic bias has emerged as a critical challenge in the age of responsible production of artificial intelligence (AI). This paper reviews recent r...

Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalization.

Fairness (also known as equity interchangeably) in machine learning is important for societal well-being, but limited public datasets hinder its progr...

Efficient pyramid channel attention network for pathological myopia recognition with pretraining-and-finetuning.

Pathological myopia (PM) is the leading ocular disease for impaired vision worldwide. Clinically, the characteristics of pathology distribution in PM ...

When Trustworthiness Meets Face: Facial Design for Social Robots.

As a technical application in artificial intelligence, a social robot is one of the branches of robotic studies that emphasizes socially communicating...

Uncertainty-aware multiple-instance learning for reliable classification: Application to optical coherence tomography.

Deep learning classification models for medical image analysis often perform well on data from scanners that were used to acquire the training data. H...

Eye-tracker and fNIRS: Using neuroscientific tools to assess the learning experience during children's educational robotics activities.

In technology education, there has been a paradigmatic shift towards student-centered approaches such as learning by doing, constructionism, and exper...

Optical imaging for diabetic retinopathy diagnosis and detection using ensemble models.

Diabetes, characterized by heightened blood sugar levels, can lead to a condition called Diabetic Retinopathy (DR), which adversely impacts the eyes d...

Applications of artificial intelligence in diagnosis of uncommon cystoid macular edema using optical coherence tomography imaging: A systematic review.

Cystoid macular edema (CME) is a sight-threatening condition often associated with inflammatory and diabetic diseases. Early detection is crucial to p...

Robot-assisted system for non-invasive wide-range flexible eye positioning and tracking in particle radiotherapy.

Particle (proton, carbon ion, or others) radiotherapy for ocular tumors is highly dependent on precise dose distribution, and any misalignment can res...

Assessing AI receptivity through a persuasion knowledge lens.

Understanding human-artificial intelligence (AI) interactions is a growing academic interest. This article conceptualizes AI as a persuasion agent and...

Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning.

Residents learn the vesico-urethral anastomosis (VUA), a key step in robot-assisted radical prostatectomy (RARP), early in their training. VUA assessm...

Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques.

The study aimed to achieve the following objectives: (1) to perform the fusion of thermal and visible tongue images with various fusion rules of discr...

Enhancing fall risk assessment: instrumenting vision with deep learning during walks.

BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typical...

Spontaneous brain activity in patients with central retinal artery occlusion: a resting-state functional MRI study using machine learning.

Central retinal artery occlusion (CRAO) is a serious eye condition that poses a risk to vision, resulting from the blockage of the central retinal art...

Diagnostic application in streptozotocin-induced diabetic retinopathy rats: A study based on Raman spectroscopy and machine learning.

Vision impairment caused by diabetic retinopathy (DR) is often irreversible, making early-stage diagnosis imperative. Raman spectroscopy emerges as a ...