AIMC Topic: Humans

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A Coupled FEM-SPH Modeling Technique to Investigate the Contractility of Biohybrid Thin Films.

Advanced biosystems
Biohybrid actuators have the potential to overcome the limitations of traditional actuators employed in robotics, thanks to the unique features of living contractile muscle cells, which can be used to power artificial elements. This paper describes a...

Facial expression monitoring system for predicting patient's sudden movement during radiotherapy using deep learning.

Journal of applied clinical medical physics
PURPOSE: Imaging, breath-holding/gating, and fixation devices have been developed to minimize setup errors so that the prescribed dose can be exactly delivered to the target volume in radiotherapy. Despite these efforts, additional patient monitoring...

Deep learning networks for the recognition and quantitation of surface-enhanced Raman spectroscopy.

The Analyst
Surface-enhanced Raman spectroscopy (SERS) based on machine learning methods has been applied in material analysis, biological detection, food safety, and intelligent analysis. However, machine learning methods generally require extra preprocessing o...

The four dimensions of contestable AI diagnostics - A patient-centric approach to explainable AI.

Artificial intelligence in medicine
The problem of the explainability of AI decision-making has attracted considerable attention in recent years. In considering AI diagnostics we suggest that explainability should be explicated as 'effective contestability'. Taking a patient-centric ap...

Behavioral Activity Recognition Based on Gaze Ethograms.

International journal of neural systems
Noninvasive behavior observation techniques allow more natural human behavior assessment experiments with higher ecological validity. We propose the use of gaze ethograms in the context of user interaction with a computer display to characterize the ...

Analyzing Factors Associated with Fatal Road Crashes: A Machine Learning Approach.

International journal of environmental research and public health
Road traffic injury accounts for a substantial human and economic burden globally. Understanding risk factors contributing to fatal injuries is of paramount importance. In this study, we proposed a model that adopts a hybrid ensemble machine learning...

Weakly-supervised learning for lung carcinoma classification using deep learning.

Scientific reports
Lung cancer is one of the major causes of cancer-related deaths in many countries around the world, and its histopathological diagnosis is crucial for deciding on optimum treatment strategies. Recently, Artificial Intelligence (AI) deep learning mode...

Deep Learning for Improved Risk Prediction in Surgical Outcomes.

Scientific reports
The Norwood surgical procedure restores functional systemic circulation in neonatal patients with single ventricle congenital heart defects, but this complex procedure carries a high mortality rate. In this study we address the need to provide an acc...

A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems.

mBio
Machine learning (ML) modeling of the human microbiome has the potential to identify microbial biomarkers and aid in the diagnosis of many diseases such as inflammatory bowel disease, diabetes, and colorectal cancer. Progress has been made toward dev...

The use of machine learning in rare diseases: a scoping review.

Orphanet journal of rare diseases
BACKGROUND: Emerging machine learning technologies are beginning to transform medicine and healthcare and could also improve the diagnosis and treatment of rare diseases. Currently, there are no systematic reviews that investigate, from a general per...