AI Medical Compendium Topic:
Delivery of Health Care

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Stakeholders' views on the organisational factors affecting application of artificial intelligence in healthcare: a scoping review protocol.

BMJ open
INTRODUCTION: Artificial intelligence (AI) offers great potential for transforming healthcare delivery leading to better patient-outcomes and more efficient care delivery. However, despite these advantages, integration of AI in healthcare has not kep...

A New Argument for No-Fault Compensation in Health Care: The Introduction of Artificial Intelligence Systems.

Health care analysis : HCA : journal of health philosophy and policy
Artificial intelligence (AI) systems advising healthcare professionals will be widely introduced into healthcare settings within the next 5-10 years. This paper considers how this will sit with tort/negligence based legal approaches to compensation f...

An Inception Convolutional Autoencoder Model for Chinese Healthcare Question Clustering.

IEEE transactions on cybernetics
Healthcare question answering (HQA) system plays a vital role in encouraging patients to inquire for professional consultation. However, there are some challenging factors in learning and representing the question corpus of HQA datasets, such as high...

Software Defect Prediction for Healthcare Big Data: An Empirical Evaluation of Machine Learning Techniques.

Journal of healthcare engineering
Software defect prediction (SDP) in the initial period of the software development life cycle (SDLC) remains a critical and important assignment. SDP is essentially studied during few last decades as it leads to assure the quality of software systems...

Towards a pragmatist dealing with algorithmic bias in medical machine learning.

Medicine, health care, and philosophy
Machine Learning (ML) is on the rise in medicine, promising improved diagnostic, therapeutic and prognostic clinical tools. While these technological innovations are bound to transform health care, they also bring new ethical concerns to the forefron...

Evaluation of machine learning algorithms for health and wellness applications: A tutorial.

Computers in biology and medicine
Research on decision support applications in healthcare, such as those related to diagnosis, prediction, treatment planning, etc., has seen strongly growing interest in recent years. This development is thanks to the increase in data availability as ...

Multi-source Seq2seq guided by knowledge for Chinese healthcare consultation.

Journal of biomedical informatics
Online healthcare consultation offers people a convenient way to consult doctors. In this paper, we aim at building a generative dialog system for Chinese healthcare consultation. As the original Seq2seq architecture tends to suffer the issue of gene...

Research perspectives on animal health in the era of artificial intelligence.

Veterinary research
Leveraging artificial intelligence (AI) approaches in animal health (AH) makes it possible to address highly complex issues such as those encountered in quantitative and predictive epidemiology, animal/human precision-based medicine, or to study host...

The concept of justifiable healthcare and how big data can help us to achieve it.

BMC medical informatics and decision making
Over the last decades, the face of health care has changed dramatically, with big improvements in what is technically feasible. However, there are indicators that the current approach to evaluating evidence in health care is not holistic and hence in...

Assessment of the Acceptability and Feasibility of Using Mobile Robotic Systems for Patient Evaluation.

JAMA network open
IMPORTANCE: Before the widespread implementation of robotic systems to provide patient care during the COVID-19 pandemic occurs, it is important to understand the acceptability of these systems among patients and the economic consequences associated ...