AI Medical Compendium Topic

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Delivery of Health Care

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Developing a Technical-Oriented Taxonomy to Define Archetypes of Conversational Agents in Health Care: Literature Review and Cluster Analysis.

Journal of medical Internet research
BACKGROUND: The evolution of artificial intelligence and natural language processing generates new opportunities for conversational agents (CAs) that communicate and interact with individuals. In the health domain, CAs became popular as they allow fo...

Application of Feedforward and Recurrent Neural Networks for Fusion of Data from Radar and Depth Sensors Applied for Healthcare-Oriented Characterisation of Persons' Gait.

Sensors (Basel, Switzerland)
In this paper, the useability of feedforward and recurrent neural networks for fusion of data from impulse-radar sensors and depth sensors, in the context of healthcare-oriented monitoring of elderly persons, is investigated. Two methods of data fusi...

Diagnostic quality model (DQM): an integrated framework for the assessment of diagnostic quality when using AI/ML.

Clinical chemistry and laboratory medicine
BACKGROUND: Laboratory medicine has reached the era where promises of artificial intelligence and machine learning (AI/ML) seem palpable. Currently, the primary responsibility for risk-benefit assessment in clinical practice resides with the medical ...

Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare.

Neural networks : the official journal of the International Neural Network Society
BACKGROUND: The idea of smart healthcare has gradually gained attention as a result of the information technology industry's rapid development. Smart healthcare uses next-generation technologies i.e., artificial intelligence (AI) and Internet of Thin...

Artificial intelligence in medicine - is too much transparency a good thing?

The Medico-legal journal
Some encouraging uses for AI in medicine will lead to potentially novel legal liability issues. Complex algorithms involve an opacity that creates problems for the medical and legal professions alike. As iatrogenic injury is common in medical malprac...

Machine Learning and Health Care: Potential Benefits and Issues.

The Journal of ambulatory care management
We discuss the potential for machine learning (ML) and artificial intelligence (AI) to improve health care, while detailing caveats and important considerations to ensure unbiased and equitable implementation. If disparities exist in the data used to...

Intelligent Physical Robots in Health Care: Systematic Literature Review.

Journal of medical Internet research
BACKGROUND: Intelligent physical robots based on artificial intelligence have been argued to bring about dramatic changes in health care services. Previous research has examined the use of intelligent physical robots in the health care context from d...

The application of machine learning to predict high-cost patients: A performance-comparison of different models using healthcare claims data.

PloS one
Our aim was to predict future high-cost patients with machine learning using healthcare claims data. We applied a random forest (RF), a gradient boosting machine (GBM), an artificial neural network (ANN) and a logistic regression (LR) to predict high...

[Artificial intelligence and ethics in healthcare-balancing act or symbiosis?].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
Artificial intelligence (AI) is becoming increasingly important in healthcare. This development triggers serious concerns that can be summarized by six major "worst-case scenarios". From AI spreading disinformation and propaganda, to a potential new ...