AI Medical Compendium Topic

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

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Creating an ignorance-base: Exploring known unknowns in the scientific literature.

Journal of biomedical informatics
BACKGROUND: Scientific discovery progresses by exploring new and uncharted territory. More specifically, it advances by a process of transforming unknown unknowns first into known unknowns, and then into knowns. Over the last few decades, researchers...

VLAD: Task-agnostic VAE-based lifelong anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Lifelong learning represents an emerging machine learning paradigm that aims at designing new methods providing accurate analyses in complex and dynamic real-world environments. Although a significant amount of research has been conducted in image cl...

Artificial intelligence in radiology - beyond the black box.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
BACKGROUND: Artificial intelligence is playing an increasingly important role in radiology. However, more and more often it is no longer possible to reconstruct decisions, especially in the case of new and powerful methods from the field of deep lear...

Logical definition-based identification of potential missing concepts in SNOMED CT.

BMC medical informatics and decision making
BACKGROUND: Biomedical ontologies are representations of biomedical knowledge that provide terms with precisely defined meanings. They play a vital role in facilitating biomedical research in a cross-disciplinary manner. Quality issues of biomedical ...

Eye for an AI: More-than-seeing, fauxtomation, and the enactment of uncertain data in digital pathology.

Social studies of science
Artificial Intelligence (AI) tools are being developed to assist with increasingly complex diagnostic tasks in medicine. This produces epistemic disruption in diagnostic processes, even in the absence of AI itself, through the datafication and digita...

Domain-adaptive message passing graph neural network.

Neural networks : the official journal of the International Neural Network Society
Cross-network node classification (CNNC), which aims to classify nodes in a label-deficient target network by transferring the knowledge from a source network with abundant labels, draws increasing attention recently. To address CNNC, we propose a do...

A multi-view co-training network for semi-supervised medical image-based prognostic prediction.

Neural networks : the official journal of the International Neural Network Society
Prognostic prediction has long been a hotspot in disease analysis and management, and the development of image-based prognostic prediction models has significant clinical implications for current personalized treatment strategies. The main challenge ...

Predicting disease genes based on multi-head attention fusion.

BMC bioinformatics
BACKGROUND: The identification of disease-related genes is of great significance for the diagnosis and treatment of human disease. Most studies have focused on developing efficient and accurate computational methods to predict disease-causing genes. ...

Health literacy in ChatGPT: exploring the potential of the use of artificial intelligence to produce academic text.

Ciencia & saude coletiva
The aim of this study was to identify and analyze the main constituent elements of text generated by ChatGPT in response to questions on an emerging topic in the academic literature in Portuguese - health literacy - and discuss how the evidence produ...

A Federated Learning-Inspired Evolutionary Algorithm: Application to Glucose Prediction.

Sensors (Basel, Switzerland)
In this paper, we propose an innovative Federated Learning-inspired evolutionary framework. Its main novelty is that this is the first time that an Evolutionary Algorithm is employed on its own to directly perform Federated Learning activity. A furth...