AIMC Journal:
Journal of the American Medical Informatics Association : JAMIA

Showing 221 to 230 of 493 articles

An analysis of the effects of limited training data in distributed learning scenarios for brain age prediction.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Distributed learning avoids problems associated with central data collection by training models locally at each site. This can be achieved by federated learning (FL) aggregating multiple models that were trained in parallel or training a s...

Multimodal attention-based deep learning for Alzheimer's disease diagnosis.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Alzheimer's disease (AD) is the most common neurodegenerative disorder with one of the most complex pathogeneses, making effective and clinically actionable decision support difficult. The objective of this study was to develop a novel mul...

Picture a data scientist: a call to action for increasing diversity, equity, and inclusion in the age of AI.

Journal of the American Medical Informatics Association : JAMIA
The lack of diversity, equity, and inclusion continues to hamper the artificial intelligence (AI) field and is especially problematic for healthcare applications. In this article, we expand on the need for diversity, equity, and inclusion, specifical...

A survey of automated methods for biomedical text simplification.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Plain language in medicine has long been advocated as a way to improve patient understanding and engagement. As the field of Natural Language Processing has progressed, increasingly sophisticated methods have been explored for the automati...

A smart, practical, deep learning-based clinical decision support tool for patients in the prostate-specific antigen gray zone: model development and validation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Despite efforts to improve screening and early detection of prostate cancer (PC), no available biomarker has shown acceptable performance in patients with prostate-specific antigen (PSA) gray zones. We aimed to develop a deep learning-base...

A scoping review of publicly available language tasks in clinical natural language processing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To provide a scoping review of papers on clinical natural language processing (NLP) shared tasks that use publicly available electronic health record data from a cohort of patients.

Identifying infected patients using semi-supervised and transfer learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Early identification of infection improves outcomes, but developing models for early identification requires determining infection status with manual chart review, limiting sample size. Therefore, we aimed to compare semi-supervised and t...

Tasks as needs: reframing the paradigm of clinical natural language processing research for real-world decision support.

Journal of the American Medical Informatics Association : JAMIA
Electronic medical records are increasingly used to store patient information in hospitals and other clinical settings. There has been a corresponding proliferation of clinical natural language processing (cNLP) systems aimed at using text data in th...

Impact of artificial intelligence on pathologists' decisions: an experiment.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The accuracy of artificial intelligence (AI) in medicine and in pathology in particular has made major progress but little is known on how much these algorithms will influence pathologists' decisions in practice. The objective of this pape...

Development and validation of a deep learning model to predict the survival of patients in ICU.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Patients in the intensive care unit (ICU) are often in critical condition and have a high mortality rate. Accurately predicting the survival probability of ICU patients is beneficial to timely care and prioritizing medical resources to im...