Exploring the CIEDE2000 thresholds for lightness, chroma, and hue differences in dentistry.

Objective: To evaluate the perceptibility and acceptability CIEDE2000 (K:K:K) thresholds for lightness, chroma and hue differences in dentistry.

Method: A Python-based program was developed to conduct a psychophysical experiment based on visual assessments of computer-simulated images of human teeth. The experiment was performed on a calibrated display.

Synthetic whole-slide image tile generation with gene expression profile-infused deep generative models.

In this work, we propose an approach to generate whole-slide image (WSI) tiles by using deep generative models infused with matched gene expression profiles. First, we train a variational autoencoder (VAE) that learns a latent, lower-dimensional representation of multi-tissue gene expression profiles. Then, we use this representation to infuse generative adversarial networks (GANs) that generate lung and brain cortex tissue tiles, resulting in a new model that we call RNA-GAN.

CIEDE2000 lightness, chroma and hue human gingiva thresholds.

Objective: To determine the visual 50:50% perceptibility and acceptability CIEDE2000 lightness, chroma and hue human gingiva thresholds.

Methods: A psychophysical experiment based on visual assessments of simulated images of human gingiva on a calibrated display was performed. A 20-obsever panel (dentists and laypersons; n=10) evaluated three subsets of simulated human gingiva: lightness subset (|ΔL/ΔE|≥ 0.

The Sunscreen for Kindergarteners (SKIN) Study trial protocol.

Background: Exposure to ultraviolet radiation (UVR) is the major modifiable risk factor for skin cancers. The majority of lifetime UVR exposure occurs before age 20, underscoring an important window for risk reduction. Incorporation of skills-based sunscreen education into school health curricula may foster the development of consistent and effective use of sunscreen among children and youth.

[Artificial intelligence in ophthalmology : Guidelines for physicians for the critical evaluation of studies].

Background: Empirical models have been an integral part of everyday clinical practice in ophthalmology since the introduction of the Sanders-Retzlaff-Kraff (SRK) formula. Recent developments in the field of statistical learning (artificial intelligence, AI) now enable an empirical approach to a wide range of ophthalmological questions with an unprecedented precision.

Objective: Which criteria must be considered for the evaluation of AI-related studies in ophthalmology?

Material And Methods: Exemplary prediction of visual acuity (continuous outcome) and classification of healthy and diseased eyes (discrete outcome) using retrospectively compiled optical coherence tomography data (50 eyes of 50 patients, 50 healthy eyes of 50 subjects).

Advancing Evidence Synthesis from Effectiveness to Implementation: Integration of Implementation Measures into Evidence Reviews.

Background: In order to close the gap between discoveries that could improve health, and widespread impact on routine health care practice, there is a need for greater attention to the factors that influence dissemination and implementation of evidence-based practices. Evidence synthesis projects (e.g.

Automated Detection of Measurements and Their Descriptors in Radiology Reports Using a Hybrid Natural Language Processing Algorithm.

Radiological measurements are reported in free text reports, and it is challenging to extract such measures for treatment planning such as lesion summarization and cancer response assessment. The purpose of this work is to develop and evaluate a natural language processing (NLP) pipeline that can extract measurements and their core descriptors, such as temporality, anatomical entity, imaging observation, RadLex descriptors, series number, image number, and segment from a wide variety of radiology reports (MR, CT, and mammogram). We created a hybrid NLP pipeline that integrates rule-based feature extraction modules and conditional random field (CRF) model for extraction of the measurements from the radiology reports and links them with clinically relevant features such as anatomical entities or imaging observations.

Weakly supervised natural language processing for assessing patient-centered outcome following prostate cancer treatment.

Background: The population-based assessment of patient-centered outcomes (PCOs) has been limited by the efficient and accurate collection of these data. Natural language processing (NLP) pipelines can determine whether a clinical note within an electronic medical record contains evidence on these data. We present and demonstrate the accuracy of an NLP pipeline that targets to assess the presence, absence, or risk discussion of two important PCOs following prostate cancer treatment: urinary incontinence (UI) and bowel dysfunction (BD).

Proposing New RadLex Terms by Analyzing Free-Text Mammography Reports.

After years of development, the RadLex terminology contains a large set of controlled terms for the radiology domain, but gaps still exist. We developed a data-driven approach to discover new terms for RadLex by mining a large corpus of radiology reports using natural language processing (NLP) methods. Our system, developed for mammography, discovers new candidate terms by analyzing noun phrases in free-text reports to extend the mammography part of RadLex.

Gender differences in limited duty time for lower limb injury.

Background: Among active-duty military personnel, lower limb musculoskeletal injuries and related conditions (injuries) frequently arise as unintended consequences of physical training. These injuries are particularly common among women. The practical impact of such injuries on temporary military occupational disability has not been estimated with precision on a large scale.

Is Accessibility to Dental Care Facilities in Rural Areas Associated with Number of Teeth in Elderly Residents?

Given that public transportation networks are less developed in rural than in urban areas, a lack of accessibility to dental care facilities could be a barrier to routine dental checkups. Thus, we hypothesized that the distance to the dental care facilities is a risk factor for tooth loss. The aim of this study was to test whether there is an association between the distance to dental care facilities, estimated by geographic information systems, and number of teeth, assessed by an oral examination, among elderly residents of a rural area in Japan.

Geographic Elevation, Car Driving, and Depression among Elderly Residents in Rural Areas: The Shimane CoHRE Study.

Given that public transportation networks are often worse in rural areas than in urban areas, it is difficult for elderly non-drivers to access health-promoting goods, services, and resources related to mental health. Moreover, geographical location, assessed by elevation, could modify this association in a rural area. The aim of this study was to test whether the association between car driving (being a driver or not) and depression, as measured by the Zung Self-Rating Depression Scale (SDS), varied by elevation.

Social disparities in dietary habits among women: Geographic Research on Wellbeing (GROW) Study.

Objective: Relationships among race/ethnicity, individual socio-economic status (SES), neighbourhood SES and acculturation are complex. We sought to answer whether: (i) race/ethnicity, individual SES and neighbourhood SES have independent effects on women's fruit and vegetable consumption (FVC); (ii) SES modifies the effects of race/ethnicity on FVC; and (iii) nativity modifies the effect of Latina ethnicity on FVC.

Design: Cross-sectional surveys from the population-based Geographic Research on Wellbeing (GROW) Study were linked with census-tract level data.

Geographic Elevation and Cognitive Function among Elderly Residents in Rural Mountainous Areas: Shimane CoHRE Study.

The aim of this study was to test whether there is an association between elevation and cognitive function among elderly residents in rural mountainous areas. Data were collected in 2012 from a cross-sectional study conducted in Ohnan Town, which is located in a rural mountainous area in the southern part of Shimane Prefecture, Japan. Cognitive function was evaluated using CADi (Cognitive Assessment for Dementia, iPad version) and elevation was estimated by using Geographic Information Systems according to the participant's address.

Accessible Transportation, Geographic Elevation, and Masticatory Ability Among Elderly Residents of a Rural Area.

Given that public transportation networks are often worse in rural areas than in urban areas, rural residents who do not drive can find it difficult to access health-promoting goods, services, and resources related to masticatory ability. Moreover, geographical location, assessed by elevation, could modify this association. The aim of this study was to test whether the association between access to transportation and masticatory ability varied by elevation.