AIMC Topic: Data Accuracy

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Towards robust multimodal ultrasound classification for liver tumor diagnosis: A generative approach to modality missingness.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In medical image analysis, combining multiple imaging modalities enhances diagnostic accuracy by providing complementary information. However, missing modalities are common in clinical settings, limiting the effectiveness of...

Federated Learning for Healthcare: Class Imbalance Mitigation and Feature Drift Detection.

Studies in health technology and informatics
Federated learning (FL) has the potential to revolutionize healthcare by enabling collaborative data analysis while keeping data decentralized. Monitoring data quality is crucial for successful FL in healthcare, as undetected issues can compromise mo...

KPRR: a novel machine learning approach for effectively capturing nonadditive effects in genomic prediction.

Briefings in bioinformatics
Nonadditive genetic effects pose significant challenges to traditional genomic selection methods for quantitative traits. Machine learning approaches, particularly kernel-based methods, offer promising solutions to overcome these limitations. In this...

Improving the Quality of Unstructured Cancer Data Using Large Language Models: A German Oncological Case Study.

Studies in health technology and informatics
With cancer being a leading cause of death globally, epidemiological and clinical cancer registration is paramount for enhancing oncological care and facilitating scientific research. However, the heterogeneous landscape of medical data presents sign...

Data Quality Matters: Suicide Intention Detection on Social Media Posts Using RoBERTa-CNN.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Suicide remains a pressing global health concern, necessitating innovative approaches for early detection and intervention. This paper focuses on identifying suicidal intentions in posts from the SuicideWatch subreddit by proposing a novel deep-learn...

[Not Available].

Ugeskrift for laeger
This review delves into the possible role of artificial intelligence (AI) in medical research, from planning to publication. AI can aid in idea generation, data analysis, and writing, with tools like chatbots and transcription systems enhancing effic...

Attention is all you need: utilizing attention in AI-enabled drug discovery.

Briefings in bioinformatics
Recently, attention mechanism and derived models have gained significant traction in drug development due to their outstanding performance and interpretability in handling complex data structures. This review offers an in-depth exploration of the pri...

Data Quality in Healthcare for the Purpose of Artificial Intelligence: A Case Study on ECG Digitalization.

Studies in health technology and informatics
The quantity of data generated within healthcare is increasing exponentially. Following this development, the interest of using data driven methodologies such as machine learning is on a steady rise. However, the quality of the data also needs to be ...

Data Quality Estimation Via Model Performance: Machine Learning as a Validation Tool.

Studies in health technology and informatics
In our recent study, the attempt to classify neurosurgical operative reports into routinely used expert-derived classes exhibited an F-score not exceeding 0.74. This study aimed to test how improving the classifier (target variable) affected the shor...