AI Medical Compendium Topic:
Delivery of Health Care

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Self-supervised learning in medicine and healthcare.

Nature biomedical engineering
The development of medical applications of machine learning has required manual annotation of data, often by medical experts. Yet, the availability of large-scale unannotated data provides opportunities for the development of better machine-learning ...

Healthcare data integration using machine learning: A case study evaluation with health information-seeking behavior databases.

Research in social & administrative pharmacy : RSAP
BACKGROUND: The amount of data in health care is rapidly rising, leading to multiple datasets generated for any given individual. Data integration involves mapping variables in different datasets together to form a combined dataset which can then be ...

Enabling Artificial Intelligence of Things (AIoT) Healthcare Architectures and Listing Security Issues.

Computational intelligence and neuroscience
A significant study has been undertaken in the areas of health care and administration of cutting-edge artificial intelligence (AI) technologies throughout the previous decade. Healthcare professionals studied smart gadgets and other medical technolo...

Using Healthcare Resources Wisely: A Predictive Support System Regarding the Severity of Patient Falls.

Journal of healthcare engineering
BACKGROUND: An injurious fall is one of the main indicators of care quality in healthcare facilities. Despite several fall screen tools being widely used to evaluate a patient's fall risk, they are frequently unable to reveal the severity level of pa...

Artificial intelligence in healthcare: a primer for medical education in radiomics.

Personalized medicine
The application of artificial intelligence (AI) to healthcare has garnered significant enthusiasm in recent years. Despite the adoption of new analytic approaches, medical education on AI is lacking. We aim to create a usable AI primer for medical ed...

Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare.

Biosensors
Artificial intelligence (AI) is a modern approach based on computer science that develops programs and algorithms to make devices intelligent and efficient for performing tasks that usually require skilled human intelligence. AI involves various subs...

Confederated learning in healthcare: Training machine learning models using disconnected data separated by individual, data type and identity for Large-Scale health system Intelligence.

Journal of biomedical informatics
BACKGROUND: A patient's health information is generally fragmented across silos because it follows how care is delivered: multiple providers in multiple settings. Though it is technically feasible to reunite data for analysis in a manner that underpi...

Artificial intelligence to improve rehabilitation care for children with developmental conditions: Some ethical considerations.

Developmental medicine and child neurology
This commentary is on the original article by Greve et al. on pages 100‐106 of this issue.

Flowing through laboratory clinical data: the role of artificial intelligence and big data.

Clinical chemistry and laboratory medicine
During the last few years, clinical laboratories have faced a sea change, from facilities producing a high volume of low-cost test results, toward a more integrated and patient-centered service. Parallel to this paradigm change, the digitalization of...