AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Knowledge Extraction of Cohort Characteristics in Research Publications.

AMIA ... Annual Symposium proceedings. AMIA Symposium
When healthcare providers review the results of a clinical trial study to understand its applicability to their practice, they typically analyze how well the characteristics of the study cohort correspond to those of the patients they see. We have pr...

Best practices for artificial intelligence in life sciences research.

Drug discovery today
We describe 11 best practices for the successful use of artificial intelligence and machine learning in pharmaceutical and biotechnology research at the data, technology and organizational management levels.

From Code to Bedside: Implementing Artificial Intelligence Using Quality Improvement Methods.

Journal of general internal medicine
Despite increasing interest in how artificial intelligence (AI) can augment and improve healthcare delivery, the development of new AI models continues to outpace adoption in existing healthcare processes. Integration is difficult because current app...

Early detection of sepsis using artificial intelligence: a scoping review protocol.

Systematic reviews
BACKGROUND: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. To decrease the high case fatality rates and morbidity for sepsis and septic shock, there is a need to increase the accuracy of early dete...

Synchronization of Nonidentical Neural Networks With Unknown Parameters and Diffusion Effects via Robust Adaptive Control Techniques.

IEEE transactions on cybernetics
This paper considers the self-synchronization and tracking synchronization issues for a class of nonidentically coupled neural networks model with unknown parameters and diffusion effects. Using the special structure of neural networks with global Li...

Reporting guidelines for clinical trials of artificial intelligence interventions: the SPIRIT-AI and CONSORT-AI guidelines.

Trials
BACKGROUND: The application of artificial intelligence (AI) in healthcare is an area of immense interest. The high profile of 'AI in health' means that there are unusually strong drivers to accelerate the introduction and implementation of innovative...

Utilization of Self-Diagnosis Health Chatbots in Real-World Settings: Case Study.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI)-driven chatbots are increasingly being used in health care, but most chatbots are designed for a specific population and evaluated in controlled settings. There is little research documenting how health consum...

A machine learning compatible method for ordinal propensity score stratification and matching.

Statistics in medicine
Although machine learning techniques that estimate propensity scores for observational studies with multivalued treatments have advanced rapidly in recent years, the development of propensity score adjustment techniques has not kept pace. While machi...

Limitations of Deep Learning Attention Mechanisms in Clinical Research: Empirical Case Study Based on the Korean Diabetic Disease Setting.

Journal of medical Internet research
BACKGROUND: Despite excellent prediction performance, noninterpretability has undermined the value of applying deep-learning algorithms in clinical practice. To overcome this limitation, attention mechanism has been introduced to clinical research as...