Refractive Surgery

The adoption of socially assistive robots for long-term care: During COVID-19 and in a post-pandemic society.

The rapid spread of COVID-19 has prompted a surge in the adoption of technology, highlighting a numb...

Accuracy and efficiency of automatic tooth segmentation in digital dental models using deep learning.

This study evaluates the accuracy and efficiency of automatic tooth segmentation in digital dental m...

Robot-Assisted Laparoscopic Calyceo-Pyelostomy for Vascular Compression of the Upper Calyx (Fraley Syndrome).

Fraley's Syndrome is a rare anatomic vascular malformation described in 1966 where an aberrant cross...

Effects of control strategies on gait in robot-assisted post-stroke lower limb rehabilitation: a systematic review.

BACKGROUND: Stroke related motor function deficits affect patients' likelihood of returning to profe...

A review on the application of deep learning for CT reconstruction, bone segmentation and surgical planning in oral and maxillofacial surgery.

Computer-assisted surgery (CAS) allows clinicians to personalize treatments and surgical interventio...

Patient Benefit and Quality of Life after Robot-Assisted Head and Neck Surgery.

Robotic systems for head and neck surgery are at different stages of technical development and clini...

Automatic Segmentation and Measurement of Choroid Layer in High Myopia for OCT Imaging Using Deep Learning.

Automatic segmentation and measurement of the choroid layer is useful in studying of related fundus ...

Automatic characterization of human embryos at day 4 post-insemination from time-lapse imaging using supervised contrastive learning and inductive transfer learning techniques.

BACKGROUND: Embryo morphology is a predictive marker for implantation success and ultimately live bi...

A Post-training Quantization Method for the Design of Fixed-Point-Based FPGA/ASIC Hardware Accelerators for LSTM/GRU Algorithms.

Recurrent Neural Networks (RNNs) have become important tools for tasks such as speech recognition, t...

A machine learning approach applied to gynecological ultrasound to predict progression-free survival in ovarian cancer patients.

In a growing number of social and clinical scenarios, machine learning (ML) is emerging as a promisi...

Validation of Soft Labels in Developing Deep Learning Algorithms for Detecting Lesions of Myopic Maculopathy From Optical Coherence Tomographic Images.

PURPOSE: It is common for physicians to be uncertain when examining some images. Models trained with...

Deep Learning for Ocular Disease Recognition: An Inner-Class Balance.

It can be challenging for doctors to identify eye disorders early enough using fundus pictures. Diag...

The clinical effects of brain-computer interface with robot on upper-limb function for post-stroke rehabilitation: a meta-analysis and systematic review.

PURPOSE: Many recent clinical studies have suggested that the combination of brain-computer interfac...

Using Robot-Based Variables during Upper Limb Robot-Assisted Training in Subacute Stroke Patients to Quantify Treatment Dose.

In post-stroke motor rehabilitation, treatment dose description is estimated approximately. The aim ...

Deep learning approach for bubble segmentation from hysteroscopic images.

Gas embolism is a potentially serious complication of hysteroscopic surgery. It is particularly nece...

Robot-assisted and traditional intensive rehabilitation therapy in the treatment of post-acute stroke patient: the experience of a standard rehabilitation ward.

Deep learning for locally advanced nasopharyngeal carcinoma prognostication based on pre- and post-treatment MRI.

PURPOSE: We aimed to predict the prognosis of advanced nasopharyngeal carcinoma (stage Ⅲ-Ⅳa) using P...

Explaining spatial accessibility to high-quality nursing home care in the US using machine learning.

In this study we measure and map the system-wide spatial accessibility to good quality nursing home ...

The robotic learning curve for a newly appointed colorectal surgeon.

Robotic colorectal surgery allows for better ergonomics, superior retraction, and fine movements in ...

Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement.

Image processing plays a crucial role in maximising diagnostic quality of positron emission tomograp...

Collection of 2429 constrained headshots of 277 volunteers for deep learning.

Deep learning has rapidly been filtrating many aspects of human lives. In particular, image recognit...