Refractive Surgery

Deep learning enables automated localization of the metastatic lymph node for thyroid cancer on I post-ablation whole-body planar scans.

The accurate detection of radioactive iodine-avid lymph node (LN) metastasis on I post-ablation whole-body planar scans (RxWBSs) is important in tracking the progression of the metastatic lymph nodes (mLNs) of patients with papillary thyroid cancer (PTC). However, severe noise artifacts and the indiscernible location of the mLN from adjacent tissues with similar gray-scale values make clinical dec...

Enhancing the Surface Properties of a Bioengineered Anterior Cruciate Ligament Matrix for Use with Point-of-Care Stem Cell Therapy.

We have previously developed a poly(-lactic) acid (PLLA) bioengineered anterior cruciate ligament (ACL) matrix that has demonstrated enhanced healing when seeded with primary ACL cells prior to implantation in a rabbit model, as compared with the matrix alone. This suggests that improving cell adhesion on the matrix may beneficially affect the healing response and long-term performance of the bioe...

Multi-view deep learning for rigid gas permeable lens base curve fitting based on Pentacam images.

Many studies in the rigid gas permeable (RGP) lens fitting field have focused on providing the best fit for patients with irregular astigmatism, a cha...

Association Rule Learning Is an Easy and Efficient Method for Identifying Profiles of Traumas and Stressors that Predict Psychopathology in Disaster Survivors: The Example of Sri Lanka.

Research indicates that psychopathology in disaster survivors is a function of both experienced trauma and stressful life events. However, such studie...

Accuracy of a deep convolutional neural network in the detection of myopic macular diseases using swept-source optical coherence tomography.

This study examined and compared outcomes of deep learning (DL) in identifying swept-source optical coherence tomography (OCT) images without myopic m...

Discriminating stress from rest based on resting-state connectivity of the human brain: A supervised machine learning study.

Acute stress induces large-scale neural reorganization with relevance to stress-related psychopathology. Here, we applied a novel supervised machine l...

Towards a fully automated surveillance of well-being status in laboratory mice using deep learning: Starting with facial expression analysis.

Assessing the well-being of an animal is hindered by the limitations of efficient communication between humans and animals. Instead of direct communic...

Achieving affective human-virtual agent communication by enabling virtual agents to imitate positive expressions.

Affective communication, communicating with emotion, during face-to-face communication is critical for social interaction. Advances in artificial inte...

Mu-net: Multi-scale U-net for two-photon microscopy image denoising and restoration.

Advances in two two-photon microscopy (2PM) have made three-dimensional (3D) neural imaging of deep cortical regions possible. However, 2PM often suff...

Prediction of Myopia in Adolescents through Machine Learning Methods.

According to literature, myopia has become the second most common eye disease in China, and the incidence of myopia is increasing year by year, and sh...

Endocannabinoid degradation inhibitors ameliorate neuronal and synaptic alterations following traumatic brain injury.

Our previous work showed that lateral fluid percussion injury to the sensorimotor cortex (SMC) of anesthetized rats increased neuronal synaptic hypere...

Training and Validation of Deep Neural Networks for the Prediction of 90-Day Post-Liver Transplant Mortality Using UNOS Registry Data.

Prediction models of post-liver transplant mortality are crucial so that donor organs are not allocated to recipients with unreasonably high probabili...

Effects of post-weaning supplementation of immunomodulatory feed ingredient on body weight and cortisol concentrations in program-fed beef heifers.

The objective of this study was to determine the effects of an immunomodulatory feed ingredient during post-weaning on growth and cortisol concentrati...

Predicting the occurrence of surgical site infections using text mining and machine learning.

In this study we propose the use of text mining and machine learning methods to predict and detect Surgical Site Infections (SSIs) using textual descr...

Optical Coherence Tomography Guided Robotic Needle Insertion for Deep Anterior Lamellar Keratoplasty.

OBJECTIVE: Deep anterior lamellar keratoplasty (DALK) significantly reduces the post-transplantation morbidity in patients eligible for partial-thickn...

Development of artificial neural network model for prediction of post-streptococcus mutans in dental caries.

BACKGROUND AND OBJECTIVE: Streptococcus mutans is the primary initiator and most common organism associated with dental caries. Prediction of post-Str...

Comparative analysis on Facebook post interaction using DNN, ELM and LSTM.

This study presents a novel research approach to predict user interaction for social media post using machine learning algorithms. The posts are conve...

Association of polymorphisms in , , and with post-induction infliximab trough level in Crohn's disease patients.

BACKGROUND: Trough levels of the post-induction serum infliximab (IFX) are associated with short-term and long-term responses of Crohn's disease patie...

Applying Machine Learning Techniques in Nomogram Prediction and Analysis for SMILE Treatment.

PURPOSE: To analyze the outcome of machine learning technique for prediction of small incision lenticule extraction (SMILE) nomogram.

Predicting post-stroke pneumonia using deep neural network approaches.

BACKGROUND AND PURPOSE: Pneumonia is a common complication after stroke, causing an increased length of hospital stay and death. Therefore, the timely...