AIMC Topic: Artificial Intelligence

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Looking beyond the hype: Applied AI and machine learning in translational medicine.

EBioMedicine
Big data problems are becoming more prevalent for laboratory scientists who look to make clinical impact. A large part of this is due to increased computing power, in parallel with new technologies for high quality data generation. Both new and old t...

Radiomics machine-learning signature for diagnosis of hepatocellular carcinoma in cirrhotic patients with indeterminate liver nodules.

European radiology
PURPOSE: To enhance clinician's decision-making by diagnosing hepatocellular carcinoma (HCC) in cirrhotic patients with indeterminate liver nodules using quantitative imaging features extracted from triphasic CT scans.

Artificial Intelligence in Nephrology: Core Concepts, Clinical Applications, and Perspectives.

American journal of kidney diseases : the official journal of the National Kidney Foundation
Artificial intelligence is playing an increasingly important role in many fields of medicine, assisting physicians in most steps of patient management. In nephrology, artificial intelligence can already be used to improve clinical care, hemodialysis ...

Using artificial intelligence to reduce diagnostic workload without compromising detection of urinary tract infections.

BMC medical informatics and decision making
BACKGROUND: A substantial proportion of microbiological screening in diagnostic laboratories is due to suspected urinary tract infections (UTIs), yet approximately two thirds of urine samples typically yield negative culture results. By reducing the ...

The future of endoscopy: Advances in endoscopic image innovations.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
The latest state of the art technological innovations have led to a palpable progression in endoscopic imaging and may facilitate standardisation of practice. One of the most rapidly evolving modalities is artificial intelligence with recent studies ...

Personalized Breast Cancer Treatments Using Artificial Intelligence in Radiomics and Pathomics.

Journal of medical imaging and radiation sciences
Progress in computing power and advances in medical imaging over recent decades have culminated in new opportunities for artificial intelligence (AI), computer vision, and using radiomics to facilitate clinical decision-making. These opportunities ar...

Artificial intelligence: Implications for the future of work.

American journal of industrial medicine
Artificial intelligence (AI) is a broad transdisciplinary field with roots in logic, statistics, cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer engineering. The modern field of AI began at a small summer w...

Feedback delays can enhance anticipatory synchronization in human-machine interaction.

PloS one
Research investigating the dynamics of coupled physical systems has demonstrated that small feedback delays can allow a dynamic response system to anticipate chaotic behavior. This counterintuitive phenomenon, termed anticipatory synchronization, has...

The virtual doctor: An interactive clinical-decision-support system based on deep learning for non-invasive prediction of diabetes.

Artificial intelligence in medicine
Artificial intelligence (AI) will pave the way to a new era in medicine. However, currently available AI systems do not interact with a patient, e.g., for anamnesis, and thus are only used by the physicians for predictions in diagnosis or prognosis. ...

Artificial intelligence and avian influenza: Using machine learning to enhance active surveillance for avian influenza viruses.

Transboundary and emerging diseases
Influenza A viruses are one of the most significant viral groups globally with substantial impacts on human, domestic animal and wildlife health. Wild birds are the natural reservoirs for these viruses, and active surveillance within wild bird popula...