AIMC Topic: Algorithms

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Confidence-based laboratory test reduction recommendation algorithm.

BMC medical informatics and decision making
BACKGROUND: We propose a new deep learning model to identify unnecessary hemoglobin (Hgb) tests for patients admitted to the hospital, which can help reduce health risks and healthcare costs.

Deep learning models challenge the prevailing assumption that face-like effects for objects of expertise support domain-general mechanisms.

Proceedings. Biological sciences
The question of whether task performance is best achieved by domain-specific, or domain-general processing mechanisms is fundemental for both artificial and biological systems. This question has generated a fierce debate in the study of expert object...

Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.

Hypertension research : official journal of the Japanese Society of Hypertension
In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hypertension (PIH) is important for both identifying high-risk women and adopting early intervention. In this study, we used four machine-learning models (...

A genetic programming-based convolutional deep learning algorithm for identifying COVID-19 cases via X-ray images.

Artificial intelligence in medicine
Evolutionary algorithms have been successfully employed to find the best structure for many learning algorithms including neural networks. Due to their flexibility and promising results, Convolutional Neural Networks (CNNs) have found their applicati...

Neural co-processors for restoring brain function: results from a cortical model of grasping.

Journal of neural engineering
A major challenge in designing closed-loop brain-computer interfaces is finding optimal stimulation patterns as a function of ongoing neural activity for different subjects and different objectives. Traditional approaches, such as those currently use...

A comparative study of data-driven models for runoff, sediment, and nitrate forecasting.

Journal of environmental management
Effective prediction of qualitative and quantitative indicators for runoff is quite essential in water resources planning and management. However, although several data-driven and model-driven forecasting approaches have been employed in the literatu...

Quasi-projective and complete synchronization of discrete-time fractional-order delayed neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper presents new theoretical results on quasi-projective synchronization (Q-PS) and complete synchronization (CS) of one kind of discrete-time fractional-order delayed neural networks (DFDNNs). At first, three new fractional difference inequal...

Artificial intelligence in medical device software and high-risk medical devices - a review of definitions, expert recommendations and regulatory initiatives.

Expert review of medical devices
INTRODUCTION: Artificial intelligence (AI) encompasses a wide range of algorithms with risks when used to support decisions about diagnosis or treatment, so professional and regulatory bodies are recommending how they should be managed.

EmbryoNet: using deep learning to link embryonic phenotypes to signaling pathways.

Nature methods
Evolutionarily conserved signaling pathways are essential for early embryogenesis, and reducing or abolishing their activity leads to characteristic developmental defects. Classification of phenotypic defects can identify the underlying signaling mec...