AIMC Topic: Medical Informatics

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Artificial intelligence and computational pathology.

Laboratory investigation; a journal of technical methods and pathology
Data processing and learning has become a spearhead for the advancement of medicine, with pathology and laboratory medicine has no exception. The incorporation of scientific research through clinical informatics, including genomics, proteomics, bioin...

Ontological representation, classification and data-driven computing of phenotypes.

Journal of biomedical semantics
BACKGROUND: The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological studies. The development of computable...

Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research.

BMJ open
OBJECTIVES: Given widespread interest in applying artificial intelligence (AI) to health data to improve patient care and health system efficiency, there is a need to understand the perspectives of the general public regarding the use of health data ...

Graphical Presentations of Clinical Data in a Learning Electronic Medical Record.

Applied clinical informatics
BACKGROUND: Complex electronic medical records (EMRs) presenting large amounts of data create risks of cognitive overload. We are designing a Learning EMR (LEMR) system that utilizes models of intensive care unit (ICU) physicians' data access pattern...

US primary care in 2029: A Delphi survey on the impact of machine learning.

PloS one
OBJECTIVE: To solicit leading health informaticians' predictions about the impact of AI/ML on primary care in the US in 2029.

A Web Application for Adrenal Incidentaloma Identification, Tracking, and Management Using Machine Learning.

Applied clinical informatics
BACKGROUND: Incidental radiographic findings, such as adrenal nodules, are commonly identified in imaging studies and documented in radiology reports. However, patients with such findings frequently do not receive appropriate follow-up, partially due...

Creating a database for health IT events via a hybrid deep learning model.

Journal of biomedical informatics
OBJECTIVE: The use of poorly designed and improperly implemented health information technology (HIT) may compound risks because it can disrupt established work patterns and encourage workarounds. Analyzing and learning from HIT events could reduce th...

Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital.

Applied clinical informatics
BACKGROUND: Hospital readmissions are a key quality metric, which has been tied to reimbursement. One strategy to reduce readmissions is to direct resources to patients at the highest risk of readmission. This strategy necessitates a robust predictiv...

Applications of Artificial Intelligence and Big Data Analytics in m-Health: A Healthcare System Perspective.

Journal of healthcare engineering
Mobile health (m-health) is the term of monitoring the health using mobile phones and patient monitoring devices etc. It has been often deemed as the substantial breakthrough in technology in this modern era. Recently, artificial intelligence (AI) an...

Cancer Informatics in 2019: Deep Learning Takes Center Stage.

Yearbook of medical informatics
OBJECTIVE: To summarize significant research contributions on cancer informatics published in 2019.