Latest AI and machine learning research in health policy for healthcare professionals.
Lately, the application or integration of Artificial Intelligence in various areas of the Healthcare domain has been a prime attraction; this includes diagnostics, medicine/drugs, medical devices, interventions/procedures, imaging, therapies as well as treatment regimes, and these areas are in direct relation with the patient care, which is the core subject of the improvements envisioned through t...
The use of Artificial Intelligence (AI) technologies within the healthcare sector is growing. However, there are differences in the speed of commercial adoption of AI across sub-sectors. We employ a dataset including news mentions and executive communications of all S&P500 Health Care Index companies to explore these differences. Pharmaceutical and medicine manufacturing companies had the earliest...
Traditionally, health data management has been EMR-based and mostly handled by health care providers. Mechanisms are needed to give patients more cont...
This paper discusses a study that aimed to elicit promising application areas and potential business models for social robotics in healthcare. For thi...
Big data is the fuel of mankind's fourth industrial revolution. Coupled with new technology such as artificial intelligence and deep learning, the pot...
Robotic systems are used to support inpatients and healthcare professionals and to improve the efficiency and quality of nursing. There is a lack of s...
Various deep learning models have been developed for different healthcare predictive tasks using Electronic Health Records and have shown promising pe...
Word embeddings are a popular approach to unsupervised learning of word relationships that are widely used in natural language processing. In this art...
This article considers recent ethical topics relating to medical AI. After a general discussion of recent medical AI innovations, and a more analytic ...
Science and technology are modifying medicine at a dizzying pace. Although access in our country to the benefits of innovations in the area of devices...
Science and technology are modifying medicine at a dizzying pace. Although access in our country to the benefits of innovations in the area of devices...
Most people are now familiar with the concepts of big data, deep learning, machine learning, and artificial intelligence (AI) and have a vague expecta...
OBJECTIVE: Active Learning (AL) attempts to reduce annotation cost (ie, time) by selecting the most informative examples for annotation. Most approach...
To date, consumer health tools available over the web suffer from serious limitations that lead to low quality health- related information. While heal...
This paper aims to present an improved bicoherence spectrum (IBS) combined with cyclic modulation spectrum (CMS) and cross-correlation that is suitabl...
For data science tools to mature and become integrated into routine clinical practice, they must add value to patient care by improving quality withou...
By integrating artificial intelligence (AI) to their practice, healthcare professions will evolve towards more efficient patient management and better...
We aimed to develop a deep learning model for the prediction of the risk of advanced colorectal cancer in Taiwanese adults. We collected data of 58152...
Patient falls, a subcategory of patient safety events, cause further harm and anxiety to patients in healthcare systems. Patient fall reports are a va...
In order to improve the level of health decision-making, based on health information resources and decision support function types, this study summari...