Related papers: Evaluation of a Data Annotation Platform for Large…
The discharge summary is a one of critical documents in the patient journey, encompassing all events experienced during hospitalization, including multiple visits, medications, tests, surgery/procedures, and admissions/discharge. Providing…
Current health policy calls for greater use of evidence based care delivery services to improve patient quality and safety outcomes. Care delivery is complex, with interacting and interdependent components that challenge traditional…
We present a comprehensive survey on the use of annotations in information visualizations, highlighting their crucial role in improving audience understanding and engagement with visual data. Our investigation encompasses empirical studies…
Data annotated by humans is a source of knowledge by describing the peculiarities of the problem and therefore fueling the decision process of the trained model. Unfortunately, the annotation process for subjective natural language…
Note-taking is a critical practice for capturing, organizing, and reflecting on information in both academic and professional settings. The recent success of large language models has accelerated the development of AI-assisted tools, yet…
Intensive care unit (ICU) data are highly irregular, heterogeneous, and temporally fragmented, posing challenges for generalizable clinical prediction. We present PULSE-ICU, a self-supervised foundation model that learns event-level ICU…
Extensive bedside monitoring in Intensive Care Units (ICUs) has resulted in complex temporal data regarding patient physiology, which presents an upscale context for clinical data analysis. In the other hand, identifying the time-series…
Large pre-trained language models (LMs) have been widely adopted in biomedical and clinical domains, introducing many powerful LMs such as bio-lm and BioELECTRA. However, the applicability of these methods to real clinical use cases is…
Optimization of patient throughput and wait time in emergency departments (ED) is an important task for hospital systems. For that reason, Emergency Severity Index (ESI) system for patient triage was introduced to help guide manual…
Our research is in the relatively unexplored area of question answering technologies for patient-specific questions over their electronic health records. A large dataset of human expert curated question and answer pairs is an important…
Bioinformatics workflows are essential for complex biological data analyses and are often described in scientific articles with source code in public repositories. Extracting detailed workflow information from articles can improve…
Data annotation is essential but highly error-prone in the development of AI-enabled perception systems (AIePS) for automated driving, and its quality directly influences model performance, safety, and reliability. However, the industry…
Segmentation in medical imaging is an essential and often preliminary task in the image processing chain, driving numerous efforts towards the design of robust segmentation algorithms. Supervised learning methods achieve excellent…
Function is increasingly recognized as an important indicator of whole-person health, although it receives little attention in clinical natural language processing research. We introduce the first public annotated dataset specifically on…
Automated decision support can accelerate tedious tasks as users can focus their attention where it is needed most. However, a key concern is whether users overly trust or cede agency to automation. In this paper, we investigate the effects…
Clinical Text Notes (CTNs) contain physicians' reasoning process, written in an unstructured free text format, as they examine and interview patients. In recent years, several studies have been published that provide evidence for the…
Data annotation and synthesis generally refers to the labeling or generating of raw data with relevant information, which could be used for improving the efficacy of machine learning models. The process, however, is labor-intensive and…
Major postoperative complications are devastating to surgical patients. Some of these complications are potentially preventable via early predictions based on intraoperative data. However, intraoperative data comprise long and fine-grained…
Information system designers face many challenges w.r.t. selecting appropriate semantic technologies and deciding on a modelling approach for their system. However, there is no clear methodology yet to evaluate "semantically enriched"…
The performance of current supervised AI systems is tightly connected to the availability of annotated datasets. Annotations are usually collected through annotation tools, which are often designed for specific tasks and are difficult to…