Diet & Nutrition

Integration of NLP2FHIR Representation with Deep Learning Models for EHR Phenotyping: A Pilot Study on Obesity Datasets.

HL7 Fast Healthcare Interoperability Resources (FHIR) is one of the current data standards for enabling electronic healthcare information exchange. Previous studies have shown that FHIR is capable of modeling both structured and unstructured data from electronic health records (EHRs). However, the capability of FHIR in enabling clinical data analytics has not been well investigated. The objective ...

CQL4NLP: Development and Integration of FHIR NLP Extensions in Clinical Quality Language for EHR-driven Phenotyping.

Lack of standardized representation of natural language processing (NLP) components in phenotyping algorithms hinders portability of the phenotyping algorithms and their execution in a high-throughput and reproducible manner. The objective of the study is to develop and evaluate a standard-driven approach - CQL4NLP - that integrates a collection of NLP extensions represented in the HL7 Fast Health...

From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations.

Self-tracking can help personalize self-management interventions for chronic conditions like type 2 diabetes (T2D), but reflecting on personal data re...

Deep learning methods allow fully automated segmentation of metacarpal bones to quantify volumetric bone mineral density.

Arthritis patients develop hand bone loss, which leads to destruction and functional impairment of the affected joints. High resolution peripheral qua...

Comparison of short- and long-term postoperative occurrences after robotic single-incision cholecystectomy versus multiport laparoscopic cholecystectomy.

BACKGROUND: Long-term outcomes of SIRC are not well established. Furthermore, SIRC is only now being considered more frequently for patients with inde...

Applying Contemporary Machine Learning Approaches to Nutrition Care Real-World Evidence: Findings From the National Quality Improvement Data Set.

Using real-world data from the Academy of Nutrition and Dietetics Health Informatics Infrastructure, we use state-of-the-art clustering techniques to ...

Impact of polyphenol-rich extracts of fruits and seeds on viability of human intestinal and liver cells .

(Kakadu plum) is a native Australian fruit consumed by Indigenous Australians for centuries. Commercial interest in has increased in recent years du...

Does Physical Activity Predict Obesity-A Machine Learning and Statistical Method-Based Analysis.

BACKGROUND: Obesity prevalence has become one of the most prominent issues in global public health. Physical activity has been recognized as a key pla...

Precision nutrition: A systematic literature review.

Precision Nutrition research aims to use personal information about individuals or groups of individuals to deliver nutritional advice that, theoretic...

Machine learning approaches to constructing predictive models of vitamin D deficiency in a hypertensive population: a comparative study.

Given the association between vitamin D deficiency and risk for cardiovascular disease, we used machine learning approaches to establish a model to p...

Robot-assisted laparoscopic surgery combined with axitinib for renal cell carcinoma and inferior vena cava tumor thrombi in a patient with severe obesity and obstructive sleep apnea-hypopnea syndrome: A case report.

Interpretable Conditional Recurrent Neural Network for Weight Change Prediction: Algorithm Development and Validation Study.

BACKGROUND: In recent years, mobile-based interventions have received more attention as an alternative to on-site obesity management. Despite increase...

Geographically weighted machine learning model for untangling spatial heterogeneity of type 2 diabetes mellitus (T2D) prevalence in the USA.

Type 2 diabetes mellitus (T2D) prevalence in the United States varies substantially across spatial and temporal scales, attributable to variations of ...

Precision medicine and machine learning towards the prediction of the outcome of potential celiac disease.

Potential Celiac Patients (PCD) bear the Celiac Disease (CD) genetic predisposition, a significant production of antihuman transglutaminase antibodies...

Machine learning models to identify low adherence to influenza vaccination among Korean adults with cardiovascular disease.

BACKGROUND: Annual influenza vaccination is an important public health measure to prevent influenza infections and is strongly recommended for cardiov...

Using Natural Language Processing and Artificial Intelligence to Explore the Nutrition and Sustainability of Recipes and Food.

In this paper, we discuss the use of natural language processing and artificial intelligence to analyze nutritional and sustainability aspects of reci...

Is the Prevalence of Vitamin D deficiency in Patients with Temporomandibular Disorder Higher than Healthy Control Group?

PURPOSE: Vitamin D plays an essential role in subchondral bone, cartilage, and periarticular muscle. This study aims to assess the prevalence of vitam...

3D microscopy and deep learning reveal the heterogeneity of crown-like structure microenvironments in intact adipose tissue.

Crown-like structures (CLSs) are adipose microenvironments of macrophages engulfing adipocytes. Their histological density in visceral adipose tissue ...

HSM6AP: a high-precision predictor for the Homo N6-methyladenosine (m^6 A) based on multiple weights and feature stitching.

Recent studies have shown that RNA methylation modification can affect RNA transcription, metabolism, splicing and stability. In addition, RNA methyla...

Supervised mutational signatures for obesity and other tissue-specific etiological factors in cancer.

Determining the etiologic basis of the mutations that are responsible for cancer is one of the fundamental challenges in modern cancer research. Diffe...