Primary Care

HarborBot: A Chatbot for Social Needs Screening.

Accessing patients' social needs is a critical challenge at emergency departments (EDs). However, most EDs do not have extra staff to administer screeners, and without personnel administration, response rates are low especially for low health literacy patients. To facilitate engagement with such low health literacy patients, we designed a chatbot - HarborBot for social needs screening. Through a s...

Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods.

Cardiotoxicity related to cancer therapies has become a serious issue, diminishing cancer treatment outcomes and quality of life. Early detection of cancer patients at risk for cardiotoxicity before cardiotoxic treatments and providing preventive measures are potential solutions to improve cancer patients' quality of life. This study focuses on predicting the development of heart failure in cancer...

Machine learning methods for microbiome studies.

Researches on the microbiome have been actively conducted worldwide and the results have shown human gut bacterial environment significantly impacts o...

Glucose outcomes of a learning-type artificial pancreas with an unannounced meal in type 1 diabetes.

BACKGROUND AND OBJECTIVES: Glycemic control with unannounced meals is the major challenge for artificial pancreas. In this study, we described the per...

A health informatics transformation model based on intelligent cloud computing - exemplified by type 2 diabetes mellitus with related cardiovascular diseases.

BACKGROUND AND OBJECTIVE: Many studies regarding health analysis request structured datasets but the legacy resources provide scattered data. This stu...

SVM-based waist circumference estimation using Kinect.

BACKGROUND AND OBJECTIVE: Conventional anthropometric studies using Kinect depth sensors have concentrated on estimating the distances between two poi...

A proposed health monitoring system using fuzzy inference system.

Due to the busy schedule of every human being in today's world, consciousness towards one's health has become quite alarming. A person suffering from ...

Automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening.

OBJECTIVE: Osteoporosis is a prevalent and treatable condition, but it remains underdiagnosed. In this study, a deep learning-based system was develop...

Applying Machine Learning to Ultrafast Shape Recognition in Ligand-Based Virtual Screening.

Ultrafast Shape Recognition (USR), along with its derivatives, are Ligand-Based Virtual Screening (LBVS) methods that condense 3-dimensional informati...

Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project.

INTRODUCTION: Around 70% to 80% of the 19 million visually disabled children in the world are due to a preventable or curable disease, if detected ear...

Vitamin D insufficiency is associated with subclinical atherosclerosis in HIV-1-infected patients on combination antiretroviral therapy.

Vitamin D insufficiency has been associated with faster progression of atherosclerosis and increased cardiovascular disease risk, but limited data ar...

The Prediction of Human Abdominal Adiposity Based on the Combination of a Particle Swarm Algorithm and Support Vector Machine.

: Abdominal adiposity is an important risk factor of chronic cardiovascular diseases, thus the prediction of abdominal adiposity and obesity can reduc...

An Artificial Neural Network-based Predictive Model to Support Optimization of Inpatient Glycemic Control.

Achieving glycemic control in critical care patients is of paramount importance, and has been linked to reductions in mortality, intensive care unit ...

Predicting 10-Year Risk of End-Organ Complications of Type 2 Diabetes With and Without Metabolic Surgery: A Machine Learning Approach.

OBJECTIVE: To construct and internally validate prediction models to estimate the risk of long-term end-organ complications and mortality in patients ...

The application of artificial intelligence (AI) techniques to identify frailty within a residential aged care administrative data set.

INTRODUCTION: Research has shown that frailty, a geriatric syndrome associated with an increased risk of negative outcomes for older people, is highly...

Policy Implications of Artificial Intelligence and Machine Learning in Diabetes Management.

PURPOSE OF REVIEW: Machine learning (ML) is increasingly being studied for the screening, diagnosis, and management of diabetes and its complications....

Factors Influencing Delivery of Cancer Survivorship Care Plans: A National Patterns of Care Study.

Nearly half of all Americans will develop cancer at least once in their lifetime. Through improved screening and treatments, the number of cancer surv...

The feature extraction of resting-state EEG signal from amnestic mild cognitive impairment with type 2 diabetes mellitus based on feature-fusion multispectral image method.

Recently, combining feature extraction and classification method of electroencephalogram (EEG) signals has been widely used in identifying mild cognit...

Automatic detection of rare pathologies in fundus photographs using few-shot learning.

In the last decades, large datasets of fundus photographs have been collected in diabetic retinopathy (DR) screening networks. Through deep learning, ...

How to achieve trustworthy artificial intelligence for health.

Artificial intelligence holds great promise in terms of beneficial, accurate and effective preventive and curative interventions. At the same time, th...