Parenting

Using Deep Convolutional Neural Networks for Image-Based Diagnosis of Nutrient Deficiencies in Rice.

Symptoms of nutrient deficiencies in rice plants often appear on the leaves. The leaf color and shape, therefore, can be used to diagnose nutrient deficiencies in rice. Image classification is an efficient and fast approach for this diagnosis task. Deep convolutional neural networks (DCNNs) have been proven to be effective in image classification, but their use to identify nutrient deficiencies in...

Case of slowly progressive type 1 diabetes mellitus with drastically reduced insulin secretory capacity after immune checkpoint inhibitor treatment for advanced renal cell carcinoma.

We encountered a 55-year-old Japanese man with advanced renal cell carcinoma and slowly progressive type 1 diabetes mellitus (SPT1DM), whose insulin secretory capacity was drastically reduced for a brief period after only one cycle of immune checkpoint inhibitor (ICI) treatment. The patient had been diagnosed with type 2 diabetes at the age of 53 years and was treated using oral hypoglycemic agent...

Deep computational pathology in breast cancer.

Deep Learning (DL) algorithms are a set of techniques that exploit large and/or complex real-world datasets for cross-domain and cross-discipline pred...

Deep learning method for localization and segmentation of abdominal CT.

Computed Tomography (CT) imaging is widely used for studying body composition, i.e., the proportion of muscle and fat tissues with applications in are...

A machine learning-based approach for estimating and testing associations with multivariate outcomes.

We propose a method for summarizing the strength of association between a set of variables and a multivariate outcome. Classical summary measures are ...

Agent-oriented Decision Support System for Business Processes Management with Genetic Algorithm Optimization: an Application in Healthcare.

Agent-based approaches have been known to be appropriate as systems and methods in medical administration in recent years. The increased attention to ...

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies.

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some ro...

Artificial intelligence mobile health platform for early detection of COVID-19 in quarantine subjects using a wearable biosensor: protocol for a randomised controlled trial.

INTRODUCTION: There is an outbreak of COVID-19 worldwide. As there is no effective therapy or vaccine yet, rigorous implementation of traditional publ...

The art of atom descriptor design.

This review provides an overview of descriptions of atoms applied to the understanding of phenomena like chemical reactivity and selectivity, pK value...

An artificial neural network approach for predicting hypertension using NHANES data.

This paper focus on a neural network classification model to estimate the association among gender, race, BMI, age, smoking, kidney disease and diabet...

The Future of Skull Base Surgery: A View Through Tinted Glasses.

In the present report, we have broadly outlined the potential advances in the field of skull base surgery, which might occur within the next 20 years ...

Age-related Macular Degeneration: Nutrition, Genes and Deep Learning-The LXXVI Edward Jackson Memorial Lecture.

PURPOSE: To evaluate the importance of nutritional supplements, dietary pattern, and genetic associations in age-related macular degeneration (AMD); a...

Using Machine Learning Methods to Develop a Short Tree-Based Adaptive Classification Test: Case Study With a High-Dimensional Item Pool and Imbalanced Data.

This study explores advanced techniques in machine learning to develop a short tree-based adaptive classification test based on an existing lengthy in...

Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study.

To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning a...

A web-based automated machine learning platform to analyze liquid biopsy data.

Liquid biopsy (LB) technologies continue to improve in sensitivity, specificity, and multiplexing and can measure an ever growing library of disease b...

Neural networks for open and closed Literature-based Discovery.

Literature-based Discovery (LBD) aims to discover new knowledge automatically from large collections of literature. Scientific literature is growing a...

Evolution of renal function in patients with severe intestinal failure on home parenteral nutrition.

BACKGROUND: Kidney disease is a frequent but underestimated complication in patients suffering from intestinal failure (IF) treated by long-term home ...

Fabrication of Carbon-Based Ionic Electromechanically Active Soft Actuators.

Ionic electromechanically active capacitive laminates are a type of smart material that move in response to electrical stimulation. Due to the soft, c...

Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.

Obesity is a global health problem with wide-reaching economic and social implications. Nutrition surveillance systems are essential to understanding ...

Systems metabolomics: from metabolomic snapshots to design principles.

Metabolomics is a rapidly expanding technology that finds increasing application in a variety of fields, form metabolic disorders to cancer, from nutr...