AIMC Topic: Humans

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A Deep Spiking Neural Network Anomaly Detection Method.

Computational intelligence and neuroscience
Cyber-attacks on specialized industrial control systems are increasing in frequency and sophistication, which means stronger countermeasures need to be implemented, requiring the designers of the equipment in question to re-evaluate and redefine thei...

Predicting Substance Use Treatment Failure with Transfer Learning.

Substance use & misuse
Transfer learning, which involves repurposing a trained model on a related task, may allow for better predictions with substance use data than models that are trained using the target data alone. This approach may also be useful for small clinical da...

Transfer Learning Approach and Nucleus Segmentation with MedCLNet Colon Cancer Database.

Journal of digital imaging
Machine learning has been recently used especially in the medical field. In the diagnosis of serious diseases such as cancer, deep learning techniques can be used to reduce the workload of experts and to produce quick solutions. The nuclei found in t...

Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT.

Radiology
Background Adrenal masses are common, but radiology reporting and recommendations for management can be variable. Purpose To create a machine learning algorithm to segment adrenal glands on contrast-enhanced CT images and classify glands as normal or...

Raman spectroscopy and FTIR spectroscopy fusion technology combined with deep learning: A novel cancer prediction method.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
According to the limited molecular information reflected by single spectroscopy, and the complementarity of FTIR spectroscopy and Raman spectroscopy, we propose a novel diagnostic technology combining multispectral fusion and deep learning. We used s...

In a pilot study, automated real-time systematic review updates were feasible, accurate, and work-saving.

Journal of clinical epidemiology
OBJECTIVES: The aim of this study is to describe and pilot a novel method for continuously identifying newly published trials relevant to a systematic review, enabled by combining artificial intelligence (AI) with human expertise.

Reconstructing the predictive architecture of the mind and brain.

Trends in cognitive sciences
Predictive processing has become an influential framework in cognitive neuroscience. However, it often lacks specificity and direct empirical support. How can we probe the nature and limits of the predictive brain? We highlight the potential of recen...

Realizing the promise of AI: a new calling for cognitive science.

Trends in cognitive sciences
Rapid progress in artificial intelligence (AI) places a new spotlight on a long-standing question: how can we best develop AI to maximize its benefits to humanity? Answering this question in a satisfying and timely way represents an exciting challeng...

Algorithms and the future of work.

American journal of industrial medicine
An algorithm refers to a series of stepwise instructions used by a machine to perform a mathematical operation. In 1955, the term artificial intelligence (AI) was coined to indicate that a machine could be programmed to duplicate human intelligence. ...

Convolutional bi-directional learning and spatial enhanced attentions for lung tumor segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Accurate lung tumor segmentation from computed tomography (CT) is complex due to variations in tumor sizes, shapes, patterns and growing locations. Learning semantic and spatial relations between different feature channels, ...