AI Medical Compendium Topic

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Subsequence and distant supervision based active learning for relation extraction of Chinese medical texts.

BMC medical informatics and decision making
In recent years, relation extraction on unstructured texts has become an important task in medical research. However, relation extraction requires a large amount of labeled corpus, manually annotating sequences is time consuming and expensive. Theref...

Joint Fusion and Detection via Deep Learning in UAV-Borne Multispectral Sensing of Scatterable Landmine.

Sensors (Basel, Switzerland)
Compared with traditional mine detection methods, UAV-based measures are more suitable for the rapid detection of large areas of scatterable landmines, and a multispectral fusion strategy based on a deep learning model is proposed to facilitate mine ...

Uncertainty Estimation with Data Augmentation for Active Learning Tasks on Health Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Supervised machine learning (ML) is revolutionising healthcare, but the acquisition of reliable labels for signals harvested from medical sensors is usually challenging, manual, and costly. Active learning can assist in establishing labels on-the-fly...

Prescriptive Method for Optimizing Cost of Data Collection and Annotation in Machine Learning of Clinical Ultrasound.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
UNLABELLED: Machine learning in medical ultrasound faces a major challenge: the prohibitive costs of producing and annotating clinical data. Optimizing the data collection and annotation will improve model training efficiency, reducing project cost a...

Selecting cardiac magnetic resonance images suitable for annotation of pulmonary arteries using an active-learning based deep learning model.

Scientific reports
An increasing and aging patient population poses a growing burden on healthcare professionals. Automation of medical imaging diagnostics holds promise for enhancing patient care and reducing manpower required to accommodate an increasing patient-popu...

AI-Assisted Cotton Grading: Active and Semi-Supervised Learning to Reduce the Image-Labelling Burden.

Sensors (Basel, Switzerland)
The assessment of food and industrial crops during harvesting is important to determine the quality and downstream processing requirements, which in turn affect their market value. While machine learning models have been developed for this purpose, t...

ChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generation.

Journal of chemical information and modeling
The incredible capabilities of generative artificial intelligence models have inevitably led to their application in the domain of drug discovery. Within this domain, the vastness of chemical space motivates the development of more efficient methods ...

Learning with AI Language Models: Guidelines for the Development and Scoring of Medical Questions for Higher Education.

Journal of medical systems
In medical and biomedical education, traditional teaching methods often struggle to engage students and promote critical thinking. The use of AI language models has the potential to transform teaching and learning practices by offering an innovative,...

Enhancing AI competence in health management: students' experiences with ChatGPT as a learning Tool.

BMC medical education
BACKGROUND: The healthcare industry has had to adapt to significant shifts caused by technological advancements, demographic changes, economic pressures, and political dynamics. These factors are reshaping the complex ecosystem in which healthcare or...

Development of an Artificial Intelligence Teaching Assistant System for Undergraduate Nursing Students: A Field Testing Study.

Computers, informatics, nursing : CIN
Keeping students engaged and motivated during online or class discussion may be challenging. Artificial intelligence has potential to facilitate active learning by enhancing student engagement, motivation, and learning outcomes. The purpose of this s...