AIMC Topic: Terminology as Topic
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Data set terminology of deep learning in medicine: a historical review and recommendation.
Japanese journal of radiology
Jun 10, 2024
Medicine and deep learning-based artificial intelligence (AI) engineering represent two distinct fields each with decades of published history. The current rapid convergence of deep learning and medicine has led to significant advancements, yet it ha...
Artificial intelligence and machine learning: Definition of terms and current concepts in critical care research.
Journal of critical care
Mar 29, 2024
With increasing computing power, artificial intelligence (AI) and machine learning (ML) have prospered, which facilitate the analysis of large datasets, especially those found in critical care. It is important to define these terminologies, to inform...
Role play with large language models.
Nature
Nov 8, 2023
As dialogue agents become increasingly human-like in their performance, we must develop effective ways to describe their behaviour in high-level terms without falling into the trap of anthropomorphism. Here we foreground the concept of role play. Cas...
Future Platforms of Robotic Surgery.
The Urologic clinics of North America
Oct 25, 2021
Among the various robotic devices that exist for urologic surgery, the most common are synergistic telemanipulator systems. Several have achieved clinical feasibility and have been licensed for use in humans: the standard da Vinci, Avatera, Hinotori,...
Automatically disambiguating medical acronyms with ontology-aware deep learning.
Nature communications
Sep 7, 2021
Modern machine learning (ML) technologies have great promise for automating diverse clinical and research workflows; however, training them requires extensive hand-labelled datasets. Disambiguating abbreviations is important for automated clinical no...
Medical-VLBERT: Medical Visual Language BERT for COVID-19 CT Report Generation With Alternate Learning.
IEEE transactions on neural networks and learning systems
Aug 31, 2021
Medical imaging technologies, including computed tomography (CT) or chest X-Ray (CXR), are largely employed to facilitate the diagnosis of the COVID-19. Since manual report writing is usually too time-consuming, a more intelligent auxiliary medical s...
A hierarchical deep learning based approach for multi-functional enzyme classification.
Protein science : a publication of the Protein Society
Jun 28, 2021
Enzymes are critical proteins in every organism. They speed up essential chemical reactions, help fight diseases, and have a wide use in the pharmaceutical and manufacturing industries. Wet lab experiments to figure out an enzyme's function are time ...
A pre-training and self-training approach for biomedical named entity recognition.
PloS one
Feb 9, 2021
Named entity recognition (NER) is a key component of many scientific literature mining tasks, such as information retrieval, information extraction, and question answering; however, many modern approaches require large amounts of labeled training dat...
A Preliminary Characterization of Canonicalized and Non-Canonicalized Section Headers Across Variable Clinical Note Types.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
In the electronic health record, the majority of clinically relevant information is stored within clinical notes. Most clinical notes follow a set organizational structure composed of canonicalized section headers that facilitate clinical review and ...
A semantic database for integrated management of image and dosimetric data in low radiation dose research in medical imaging.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Medical ionizing radiation procedures and especially medical imaging are a non negligible source of exposure to patients. Whereas the biological effects of high absorbed doses are relatively well known, the effects of low absorbed doses are still deb...
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