AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Teleoperator-Robot-Human Interaction in Manufacturing: Perspectives from Industry, Robot Manufacturers, and Researchers.

IISE transactions on occupational ergonomics and human factors
OCCUPATIONAL APPLICATIONSIndustrial robots have become an important aspect in modern industry. In the context of human-robot collaboration, enabling teleoperated robots to work in close proximity to local/onsite humans can provide new opportunities t...

Applicability of Spatial Technology in Cancer Research.

Cancer research and treatment
This review explores spatial mapping technologies in cancer research, highlighting their crucial role in understanding the complexities of the tumor microenvironment (TME). The TME, which is an intricate ecosystem of diverse cell types, has a signifi...

Machine Learning and Health Science Research: Tutorial.

Journal of medical Internet research
Machine learning (ML) has seen impressive growth in health science research due to its capacity for handling complex data to perform a range of tasks, including unsupervised learning, supervised learning, and reinforcement learning. To aid health sci...

Extracting Spatio-Temporal Trends in Medical Research Prioritization Through Natural Language Processing of Case Report Abstracts.

Studies in health technology and informatics
Medical research prioritization is an important aspect of decision-making by researchers and relevant stakeholders. The ever-increasing availability of technology and data has opened doors to new discoveries and new questions. This makes it difficult...

Pneumonia detection based on RSNA dataset and anchor-free deep learning detector.

Scientific reports
Pneumonia is a highly lethal disease, and research on its treatment and early screening tools has received extensive attention from researchers. Due to the maturity and cost reduction of chest X-ray technology, and with the development of artificial ...

Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis.

GigaScience
BACKGROUND: Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding consider...

A scoping review of fair machine learning techniques when using real-world data.

Journal of biomedical informatics
OBJECTIVE: The integration of artificial intelligence (AI) and machine learning (ML) in health care to aid clinical decisions is widespread. However, as AI and ML take important roles in health care, there are concerns about AI and ML associated fair...

Artificial intelligence and illusions of understanding in scientific research.

Nature
Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might improve research. Why are AI tools so attractive and what are the risks of implementing them across the research pipeline? Here we develop a taxonomy of ...