Health Policy

Prediction of patient evolution in terms of Clinical Risk Groups form routinely collected data using machine learning.

Chronicity is a problem that is affecting quality of life and increasing healthcare costs worldwide. Predictive tools can help mitigate these effects by encouraging the patients' and healthcare system's proactivity. This research work uses supervised learning techniques to build a predictive model of the healthcare status of a chronic patient, using Clinical Risk Groups (CRGs) as a measure of chro...

Deep Learning with Convolutional Neural Network for detecting microsleep states from EEG: A comparison between the oversampling technique and cost-based learning.

Any occupation which involves critical decision making in real-time requires attention and concentration. When repetitive and expanded working periods are encountered, it can result in microsleeps. Microsleeps are complete lapses in which a subject involuntarily stops responding to the task that they are currently performing due to temporary interruptions in visual-motor and cognitive coordination...

Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges.

Combinations of healthcare claims data with additional datasets provide large and rich sources of information. The dimensionality and complexity of th...

Digital transformation in healthcare - architectures of present and future information technologies.

Healthcare providers all over the world are faced with a single challenge: the need to improve patient outcomes while containing costs. Drivers includ...

Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery.

BACKGROUND: This paper aims to move the debate forward regarding the potential for artificial intelligence (AI) and autonomous robotic surgery with a ...

Big Data Cohort Extraction for Personalized Statin Treatment and Machine Learning.

The creation of big clinical data cohorts for machine learning and data analysis require a number of steps from the beginning to successful completion...

Characteristics of Transactive Relationship Phenomena among Older adults, Care Workers as Intermediaries, and the Pepper Robot with Care Prevention Gymnastics Exercises.

Healthcare for older adults is a significant problem in Japan and in other developed countries. To address this problem, healthcare robots, now realiz...

Clinical Integration of Digital Solutions in Health Care: An Overview of the Current Landscape of Digital Technologies in Cancer Care.

Digital health constitutes a merger of both software and hardware technology with health care delivery and management, and encompasses a number of dom...

Evaluation of a protocol for reducing the microbial contamination of dental unit water.

Biofilm on dental unit waterlines can spread microbial contamination in the water. The aim of this study was to investigate microbial contamination of...

Development of machine learning algorithms for prediction of discharge disposition after elective inpatient surgery for lumbar degenerative disc disorders.

OBJECTIVEIf not anticipated and prearranged, hospital stay can be prolonged while the patient awaits placement in a rehabilitation unit or skilled nur...

A telehealth system for automated diagnosis of asthma and chronical obstructive pulmonary disease.

This paper presents the development and real-time testing of an automated expert diagnostic telehealth system for the diagnosis of 2 respiratory disea...

[The urgent need for a new ecosystem in healthcare].

The key performance indicators in healthcare illustrate that the system we run nowadays is no longer sustainable. There is an urgent need for fundamen...

A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection.

A peripherally inserted central catheter (PICC) is a thin catheter that is inserted via arm veins and threaded near the heart, providing intravenous a...

Implementation of Enterprise Imaging Strategy at a Chinese Tertiary Hospital.

Medical images have become increasingly important in clinical practice and medical research, and the need to manage images at the hospital level has b...

Using Unsupervised Machine Learning to Identify Subgroups Among Home Health Patients With Heart Failure Using Telehealth.

This study explored the use of unsupervised machine learning to identify subgroups of patients with heart failure who used telehealth services in the ...

The potential for machine learning algorithms to improve and reduce the cost of 3-dimensional printing for surgical planning.

INTRODUCTION: 3D-printed anatomical models play an important role in medical and research settings. The recent successes of 3D anatomical models in he...

An Automated Technique to Construct a Knowledge Base of Traditional Chinese Herbal Medicine for Cancers: An Exploratory Study for Breast Cancer.

Traditional Chinese Medicine utilization has rapidly increased worldwide. However, there is limited database provides the information of TCM herbs and...

Comparative Analysis of Algorithmic Approaches for Auto-Coding with ICD-10-AM and ACHI.

Clinical coding is done using ICD-10-AM (International Classification of Diseases, version 10, Australian Modification) and ACHI (Australian Classific...

Computational health economics for identification of unprofitable health care enrollees.

Health insurers may attempt to design their health plans to attract profitable enrollees while deterring unprofitable ones. Such insurers would not be...

OLS Client and OLS Dialog: Open Source Tools to Annotate Public Omics Datasets.

The availability of user-friendly software to annotate biological datasets and experimental details is becoming essential in data management practices...