Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2018
OBJECTIVE: Develop an approach, One-class-at-a-time, for triaging psychiatric patients using machine learning on textual patient records. Our approach aims to automate the triaging process and reduce expert effort while providing high classification ...
Journal of the American Medical Informatics Association : JAMIA
Jul 1, 2018
OBJECTIVE: Medical word sense disambiguation (WSD) is challenging and often requires significant training with data labeled by domain experts. This work aims to develop an interactive learning algorithm that makes efficient use of expert's domain kno...
Uncertainty in text-based medical reports has long been recognized as problematic, frequently resulting in misunderstanding and miscommunication. One strategy for addressing the negative clinical ramifications of report uncertainty would be the creat...
A significant volume of medical data remains unstructured. Natural language processing (NLP) and machine learning (ML) techniques have shown to successfully extract insights from radiology reports. However, the codependent effects of NLP and ML in th...
BMC medical informatics and decision making
Mar 22, 2018
BACKGROUND: Temporal expression extraction and normalization is a fundamental and essential step in clinical text processing and analyzing. Though a variety of commonly used NLP tools are available for medical temporal information extraction, few wor...
International journal of medical informatics
Mar 1, 2018
OBJECTIVE: In this work, we propose an ontology-driven approach to identify events and their attributes from episodes of care included in medical reports written in Italian. For this language, shared resources for clinical information extraction are ...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 1, 2018
Recent studies documented the importance of individuality and heterogeneity in care planning. In practice, varying behavioral responses are revealed in patients' care management (CM) records. However, today's care programs are structured around popul...
In recent years, the amount of video content created and uploaded to the Internet has grown exponentially. Video content has unique accessibility challenges: indexing, transcribing, and searching video has always been very labor intensive, and there ...
Many real-world medical datasets contain some proportion of missing (attribute) values. In general, missing value imputation can be performed to solve this problem, which is to provide estimations for the missing values by a reasoning process based o...