About this Research Topic
Advances in deep learning, natural language processing, and information retrieval using data from Electronic Health Records (EHRs) show great promise in improving our knowledge of healthcare and medicine overall. These techniques permit a hitherto unprecedented analysis of large and unstructured datasets that would otherwise be intractable. This allows advances such as finding relevant patterns and clusters in data, predicting treatment suitability and outcome, or identifying outliers and healthcare gaps. Artificial Intelligence holds great promise when it comes to the development of support systems to aid clinical decision making in the coming years.
This Research Topic invites new contributions in the field of Natural Language Processing and Information Retrieval that use textual data retrieved from EHRs or other medical data sources applied to advances in healthcare and medicine. The main goal is to gather novel methodologies, and examples of their translational use in clinical practice, as well as to identify the strengths and weaknesses of Artificial Intelligence in these fields.
We welcome submissions of Original Research, Systematic Reviews, Methods, Clinical Trials, Case Reports, Data Reports and Brief Research Reports addressing the development, improvement, or examples of using methods or algorithms including but not limited to:
- Natural Language Processing techniques applied to EHR notes or other forms of EHR textual data
- Information Retrieval techniques in EHR or other textual medical data
- Other methods of EHR data mining and potential uses
- Multimodal Deep Learning in medicine/healthcare
- Abstractive Summarization of EHR unstructured data and potential uses
- Other forms of data analytics of text obtained from EHRs or other medical data sources
This Research Topic invites new contributions in the field of Natural Language Processing and Information Retrieval that use textual data retrieved from EHRs or other medical data sources applied to advances in healthcare and medicine. The main goal is to gather novel methodologies, and examples of their translational use in clinical practice, as well as to identify the strengths and weaknesses of Artificial Intelligence in these fields.
We welcome submissions of Original Research, Systematic Reviews, Methods, Clinical Trials, Case Reports, Data Reports and Brief Research Reports addressing the development, improvement, or examples of using methods or algorithms including but not limited to:
- Natural Language Processing techniques applied to EHR notes or other forms of EHR textual data
- Information Retrieval techniques in EHR or other textual medical data
- Other methods of EHR data mining and potential uses
- Multimodal Deep Learning in medicine/healthcare
- Abstractive Summarization of EHR unstructured data and potential uses
- Other forms of data analytics of text obtained from EHRs or other medical data sources
Keywords: Artificial Intelligence, Natural Language Processing, Information Retrieval, Data Mining, Electronic Health Records
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
