AIMC Topic: Delivery of Health Care

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Rise of the Machines: Artificial Intelligence and the Clinical Laboratory.

The journal of applied laboratory medicine
BACKGROUND: Artificial intelligence (AI) is rapidly being developed and implemented to augment and automate decision-making across healthcare systems. Being an essential part of these systems, laboratories will see significant growth in AI applicatio...

A NLP Pipeline for the Automatic Extraction of Microorganisms Names from Microbiological Notes.

Studies in health technology and informatics
According to the "Istituto Superiore di Sanita'" (ISS), hospital infections are the most frequent and serious complication of health care. This constitutes a real health emergency which requires incisive and joint action at all levels of the local an...

A survey of extant organizational and computational setups for deploying predictive models in health systems.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Artificial intelligence (AI) and machine learning (ML) enabled healthcare is now feasible for many health systems, yet little is known about effective strategies of system architecture and governance mechanisms for implementation. Our obje...

Natural language word embeddings as a glimpse into healthcare language and associated mortality surrounding end of life.

BMJ health & care informatics
OBJECTIVES: To clarify real-world linguistic nuances around dying in hospital as well as inaccuracy in individual-level prognostication to support advance care planning and personalised discussions on limitation of life sustaining treatment (LST).

Machine Learning for Medical Coding in Healthcare Surveys.

Vital and health statistics. Ser. 1, Programs and collection procedures
Objectives Medical coding, or the translation of healthcare information into numeric codes, is expensive and time intensive. This exploratory study evaluates the use of machine learning classifiers to perform automated medical coding for large statis...

Evaluation framework to guide implementation of AI systems into healthcare settings.

BMJ health & care informatics
OBJECTIVES: To date, many artificial intelligence (AI) systems have been developed in healthcare, but adoption has been limited. This may be due to inappropriate or incomplete evaluation and a lack of internationally recognised AI standards on evalua...

Equitable Implementation of Artificial Intelligence in Medical Imaging: What Can be Learned from Implementation Science?

PET clinics
Artificial intelligence (AI) has been rapidly adopted in various health care domains. Molecular imaging, accordingly, has demonstrated growing academic and commercial interest in AI. Unprepared and inequitable implementation and scale-up of AI in hea...

Trading off accuracy and explainability in AI decision-making: findings from 2 citizens' juries.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To investigate how the general public trades off explainability versus accuracy of artificial intelligence (AI) systems and whether this differs between healthcare and non-healthcare scenarios.

Interpretable disease prediction using heterogeneous patient records with self-attentive fusion encoder.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We propose an interpretable disease prediction model that efficiently fuses multiple types of patient records using a self-attentive fusion encoder. We assessed the model performance in predicting cardiovascular disease events, given the r...