AIMC Topic: Artificial Intelligence

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A Brief History of AI: How to Prevent Another Winter (A Critical Review).

PET clinics
Artificial intelligence has witnessed exponential growth in the past decade. Advances in computing power and the design of sophisticated artificial intelligence algorithms have enabled computers to outperform humans in a variety of tasks. Yet, artifi...

Achieving Expert-Level Interpretation of Serum Protein Electrophoresis through Deep Learning Driven by Human Reasoning.

Clinical chemistry
BACKGROUND: Serum protein electrophoresis (SPE) is a common clinical laboratory test, mainly indicated for the diagnosis and follow-up of monoclonal gammopathies. A time-consuming and potentially subjective human expertise is required for SPE analysi...

Algorithmic prognostication in critical care: a promising but unproven technology for supporting difficult decisions.

Current opinion in critical care
PURPOSE OF REVIEW: Patients, surrogate decision makers, and clinicians face weighty and urgent decisions under uncertainty in the ICU, which could be aided by risk prediction. Although emerging artificial intelligence/machine learning (AI/ML) algorit...

Introduction to Artificial Intelligence and Machine Learning for Pathology.

Archives of pathology & laboratory medicine
CONTEXT.—: Recent developments in machine learning have stimulated intense interest in software that may augment or replace human experts. Machine learning may impact pathology practice by offering new capabilities in analysis, interpretation, and ou...

Advances of Artificial Intelligence Application in Medical Imaging of Ovarian Cancers.

Chinese medical sciences journal = Chung-kuo i hsueh k'o hsueh tsa chih
Ovarian cancer is one of the three most common gynecological cancers in the world, and is regarded as a priority in terms of women's cancer. In the past few years, many researchers have attempted to develop and apply artificial intelligence (AI) tech...

Neuromorphic learning with Mott insulator NiO.

Proceedings of the National Academy of Sciences of the United States of America
Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence fou...