AIMC Topic: Artificial Intelligence

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Recent Advances in Self-Powered Piezoelectric and Triboelectric Sensors: From Material and Structure Design to Frontier Applications of Artificial Intelligence.

Sensors (Basel, Switzerland)
The development of artificial intelligence and the Internet of things has motivated extensive research on self-powered flexible sensors. The conventional sensor must be powered by a battery device, while innovative self-powered sensors can provide po...

Evaluation of a Novel Artificial Intelligence System to Monitor and Assess Energy and Macronutrient Intake in Hospitalised Older Patients.

Nutrients
Malnutrition is common, especially among older, hospitalised patients, and is associated with higher mortality, longer hospitalisation stays, infections, and loss of muscle mass. It is therefore of utmost importance to employ a proper method for diet...

[EMPAIA-ecosystem for pathology diagnostics with AI assistance].

Der Pathologe
Applications of deep learning and other artificial intelligence techniques play an increasing role in pathological research. In contrast to research, applications in clinical routine are rare so far, although the first certified solutions have alread...

Radiogenomics and Artificial Intelligence Approaches Applied to Cardiac Computed Tomography Angiography and Cardiac Magnetic Resonance for Precision Medicine in Coronary Heart Disease: A Systematic Review.

Circulation. Cardiovascular imaging
The risk of coronary heart disease (CHD) clinical manifestations and patient management is estimated according to risk scores accounting multifactorial risk factors, thus failing to cover the individual cardiovascular risk. Technological improvements...

Cluster-Based Mutual Fund Classification and Price Prediction Using Machine Learning for Robo-Advisors.

Computational intelligence and neuroscience
The rise of FinTech has been meteoric in China. Investing in mutual funds through robo-advisor has become a new innovation in the wealth management industry. In recent years, machine learning, especially deep learning, has been widely used in the fin...

Strengths and caveats of identifying resistance genes from whole genome sequencing data.

Expert review of anti-infective therapy
INTRODUCTION: Antimicrobial resistance (AMR) continues to present major challenges to modern healthcare. Recent advances in whole-genome sequencing (WGS) have made the rapid molecular characterization of AMR a realistic possibility for diagnostic lab...

Systematic Review of Health Economic Evaluations Focused on Artificial Intelligence in Healthcare: The Tortoise and the Cheetah.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: This study aimed to systematically review recent health economic evaluations (HEEs) of artificial intelligence (AI) applications in healthcare. The aim was to discuss pertinent methods, reporting quality and challenges for future implemen...

Deep Learning for Radiotherapy Outcome Prediction Using Dose Data - A Review.

Clinical oncology (Royal College of Radiologists (Great Britain))
Artificial intelligence, and in particular deep learning using convolutional neural networks, has been used extensively for image classification and segmentation, including on medical images for diagnosis and prognosis prediction. Use in radiotherapy...

Diagnosing onychomycosis: A step forward?

Journal of cosmetic dermatology
BACKGROUND AND AIMS: There are a number of available methods for diagnosing onychomycosis, but more emerge as technology advances. This review briefly discusses the common diagnostic methods, the use of artificial intelligence (AI) as a diagnostic to...