AIMC Topic: Machine Learning

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There Can Be no Other Reason for this Behavior: Issues in the Ascription of Knowledge to Humans and AI.

Integrative psychological & behavioral science
While machine learning techniques have been used to model categorization/decision making tasks that are beyond the capabilities of traditional AI, these new models are typically uninterpretable, i.e., the reasons for their decisions are not clear. So...

[Application and progress of artificial intelligence technology in gastric cancer diagnosis and treatment].

Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery
Artificial intelligence (AI) is one of the most rapidly evolving fields in biomedicine during the past decade. Represented by radiomics, machine learning and deep neural network, AI has been increasingly favored by researchers due to its ability to o...

Machine Learning and Artificial Intelligence in Toxicological Sciences.

Toxicological sciences : an official journal of the Society of Toxicology
Machine learning and artificial intelligence approaches have revolutionized multiple disciplines, including toxicology. This review summarizes representative recent applications of machine learning and artificial intelligence approaches in different ...

Information Geometrically Generalized Covariate Shift Adaptation.

Neural computation
Many machine learning methods assume that the training and test data follow the same distribution. However, in the real world, this assumption is often violated. In particular, the marginal distribution of the data changes, called covariate shift, is...

A framework for the oversight and local deployment of safe and high-quality prediction models.

Journal of the American Medical Informatics Association : JAMIA
Artificial intelligence/machine learning models are being rapidly developed and used in clinical practice. However, many models are deployed without a clear understanding of clinical or operational impact and frequently lack monitoring plans that can...

Pre-trained models, data augmentation, and ensemble learning for biomedical information extraction and document classification.

Database : the journal of biological databases and curation
Large volumes of publications are being produced in biomedical sciences nowadays with ever-increasing speed. To deal with the large amount of unstructured text data, effective natural language processing (NLP) methods need to be developed for various...

Machine fault detection methods based on machine learning algorithms: A review.

Mathematical biosciences and engineering : MBE
Preventive identification of mechanical parts failures has always played a crucial role in machine maintenance. Over time, as the processing cycles are repeated, the machinery in the production system is subject to wear with a consequent loss of tech...

Deep learning models for RNA secondary structure prediction (probably) do not generalize across families.

Bioinformatics (Oxford, England)
MOTIVATION: The secondary structure of RNA is of importance to its function. Over the last few years, several papers attempted to use machine learning to improve de novo RNA secondary structure prediction. Many of these papers report impressive resul...

Endoluminal larynx anatomy model - towards facilitating deep learning and defining standards for medical images evaluation with artificial intelligence algorithms.

Otolaryngologia polska = The Polish otolaryngology
The pioneering nature of this work covers the answers to two questions: (1) Is an up-to-date anatomical model of the larynx needed for modern endoscopic diagnostics, and (2) can such a digital segmentation model be utilized for deep learning purposes...