AI Medical Compendium Topic:
Delivery of Health Care

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Users' ambivalent sense of security with humanoid robots in healthcare.

Informatics for health & social care
Humanoid robots have already been shown to be useful in healthcare. To ensure successful interactions with humanoid robots, is it essential that the factors that influence users' sense of security be understood. Ensuring patients' sense of security i...

Use and Control of Artificial Intelligence in Patients Across the Medical Workflow: Single-Center Questionnaire Study of Patient Perspectives.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) is gaining increasing importance in many medical specialties, yet data on patients' opinions on the use of AI in medicine are scarce.

Artificial intelligence (AI) in medicine as a strategic valuable tool.

The Pan African medical journal
Humans' creativity led to machines that outperform human capabilities in terms of workload, effectiveness, precision, endurance, strength, and repetitiveness. It has always been a vision and a way to transcend the existence and to give more sense to ...

Artificial intelligence for good health: a scoping review of the ethics literature.

BMC medical ethics
BACKGROUND: Artificial intelligence (AI) has been described as the "fourth industrial revolution" with transformative and global implications, including in healthcare, public health, and global health. AI approaches hold promise for improving health ...

Interdisciplinary collaboration between nursing and engineering in health care: A scoping review.

International journal of nursing studies
BACKGROUND: Due to the rapid advancements in precision medicine and artificial intelligence, interdisciplinary collaborations between nursing and engineering have emerged. Although engineering is vital in solving complex nursing problems and advancin...

Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey.

IEEE transactions on neural networks and learning systems
Brain tumor is one of the most dangerous cancers in people of all ages, and its grade recognition is a challenging problem for radiologists in health monitoring and automated diagnosis. Recently, numerous methods based on deep learning have been pres...

Involvement of Machine Learning Tools in Healthcare Decision Making.

Journal of healthcare engineering
In the present day, there are many diseases which need to be identified at their early stages to start relevant treatments. If not, they could be uncurable and deadly. Due to this reason, there is a need of analysing complex medical data, medical rep...

Augmentation in Healthcare: Augmented Biosignal Using Deep Learning and Tensor Representation.

Journal of healthcare engineering
In healthcare applications, deep learning is a highly valuable tool. It extracts features from raw data to save time and effort for health practitioners. A deep learning model is capable of learning and extracting the features from raw data by itself...

Timely and Efficient AI Insights on EHR: System Design.

AMIA ... Annual Symposium proceedings. AMIA Symposium
A patient's electronic health record (EHR) contains extensive documentation of the patient's medical history but is difficult for clinicians to review and find what they are looking for under the time constraints of the clinical setting. Although rec...

Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The potential of Reinforcement Learning (RL) has been demonstrated through successful applications to games such as Go and Atari. However, while it is straightforward to evaluate the performance of an RL algorithm in a game setting by simply using it...