Refractive Surgery

Sensor-based particle mass prediction of lightweight packaging waste using machine learning algorithms.

Sensor-based material flow characterization (SBMC) promises to improve the performance of future-generation sorting plants by enabling new applications like automatic quality monitoring or process control. Prerequisite for this is the derivation of mass-based material flow characteristics from pixel-based sensor data, which requires known individual particle masses. Since particle masses cannot be...

Development of deep learning-based detecting systems for pathologic myopia using retinal fundus images.

Globally, cases of myopia have reached epidemic levels. High myopia and pathological myopia (PM) are the leading cause of visual impairment and blindness in China, demanding a large volume of myopia screening tasks to control the rapid growing myopic prevalence. It is desirable to develop the automatically intelligent system to facilitate these time- and labor- consuming tasks. In this study, we d...

Deceptive Online Content Detection Using Only Message Characteristics and a Machine Learning Trained Expert System.

This paper considers the use of a post metadata-based approach to identifying intentionally deceptive online content. It presents the use of an inhere...

Estimation of current and post-treatment retinal function in chronic central serous chorioretinopathy using artificial intelligence.

Refined understanding of the association of retinal microstructure with current and future (post-treatment) function in chronic central serous chorior...

Impact of Early Exposure to Robotic Surgery Among Pre-clinical Medical Students on Career Choice and Simulation Skills.

We aimed to assess whether early exposure of medical students to robotic surgery training influences their interest in a surgical career and improves ...

Graph Attention Feature Fusion Network for ALS Point Cloud Classification.

Classification is a fundamental task for airborne laser scanning (ALS) point cloud processing and applications. This task is challenging due to outdoo...

Does adoption of new technology increase surgical volume? The robotic inguinal hernia repair model.

Robotic Inguinal Hernia repair has been associated with higher costs but shorter length of stay. Robotic surgery is an appealing option for patients u...

Robot-assisted pancreatic surgery-optimized operating procedures: set-up, port placement, surgical steps.

Even in most complex surgical settings, recent advances in minimal-invasive technologies have made the application of robotic-assisted devices more vi...

Revisiting performance metrics for prediction with rare outcomes.

Machine learning algorithms are increasingly used in the clinical literature, claiming advantages over logistic regression. However, they are generall...

Automatic segmentation of gadolinium-enhancing lesions in multiple sclerosis using deep learning from clinical MRI.

Gadolinium-enhancing lesions reflect active disease and are critical for in-patient monitoring in multiple sclerosis (MS). In this work, we have devel...

Predicting post-operative right ventricular failure using video-based deep learning.

Despite progressive improvements over the decades, the rich temporally resolved data in an echocardiogram remain underutilized. Human assessments redu...

Saliency-guided deep learning network for automatic tumor bed volume delineation in post-operative breast irradiation.

Efficient, reliable and reproducible target volume delineation is a key step in the effective planning of breast radiotherapy. However, post-operative...

Implementation of a standardized robotic assistant surgical training curriculum.

Since 2000, robotic-assisted surgery has rapidly expanded into almost every surgical sub-specialty. Despite the popularity of robotic surgery across t...

Automatic detection of pathological myopia using machine learning.

Pathological myopia is a severe case of myopia, i.e., nearsightedness. Pathological myopia is also known as degenerative myopia because it ultimately ...

Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions.

Muscle fat infiltration (MFI) has been widely reported across cervical spine disorders. The quantification of MFI requires time-consuming and rater-de...

DeepUWF: An Automated Ultra-Wide-Field Fundus Screening System via Deep Learning.

The emerging ultra-wide field of view (UWF) fundus color imaging is a powerful tool for fundus screening. However, manual screening is labor-intensive...

A geometry-guided deep learning technique for CBCT reconstruction.

Although deep learning (DL) technique has been successfully used for computed tomography (CT) reconstruction, its implementation on cone-beam CT (CBCT...

Deep Learning-Guided Fiberoptic Raman Spectroscopy Enables Real-Time Diagnosis and Assessment of Nasopharyngeal Carcinoma and Post-treatment Efficacy during Endoscopy.

In this work, we develop a deep learning-guided fiberoptic Raman diagnostic platform to assess its ability of real-time nasopharyngeal carcinoma (NPC...

Machine learning-based preoperative datamining can predict the therapeutic outcome of sleep surgery in OSA subjects.

Increasing recognition of anatomical obstruction has resulted in a large variety of sleep surgeries to improve anatomic collapse of obstructive sleep ...

DeepEMhancer: a deep learning solution for cryo-EM volume post-processing.

Cryo-EM maps are valuable sources of information for protein structure modeling. However, due to the loss of contrast at high frequencies, they genera...