How can nurses contribute to machine learning through the assistance of obtaining knowledge and skills to better support patients?
By evaluating technology and filling data gaps
By simply accessing and using information
By studying statistics to understand the algorithms
By gathering patient data
The Correct Answer is A
A. By evaluating technology and filling data gaps. – Nurses can contribute by identifying gaps in data that machine learning models need to improve accuracy, and by assessing technology to ensure it meets clinical needs and complements patient care.
B. By simply accessing and using information. – Access alone does not contribute significantly to machine learning; active data input and gap identification are more effective.
C. By studying statistics to understand the algorithms. – Studying algorithms helps understand machine learning but does not directly contribute to its function or data generation.
D. By gathering patient data. – While gathering data is helpful, without evaluating technology and addressing data gaps, it doesn’t fully contribute to machine learning model improvement.
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Correct Answer is A
Explanation
A. Sources such as PubMed. – PubMed is a database of peer-reviewed medical literature, providing access to high-quality research and systematic reviews, often with high levels of evidence.
B. Recommended readings from physicians. – Physician recommendations may vary in quality and are not guaranteed to be based on the highest level of evidence or peer-reviewed sources.
C. Comprehensive searches on Google and other search engines. – These searches yield mixed sources of varying quality and do not necessarily prioritize high-level evidence-based research.
D. Magazine and newspaper articles. – These are typically not peer-reviewed or scientifically rigorous, often intended for the general public rather than professionals, and may not rely on high levels of evidence.
Correct Answer is C
Explanation
A. Anesthesia information management system. – This system is focused on managing anesthesia-related data and does not handle imaging bookings.
B. Critical care information system. – This system manages data related to critical care patients but is not involved in scheduling MRI exams.
C. Radiology-information system. – This system is specifically designed to manage imaging procedures, including scheduling and tracking MRI exams.
D. Operating room information system. – This system focuses on managing surgical procedures and scheduling within the operating room and does not cover imaging like MRIs.