AIMC Topic: Humans

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Detection of shallow anterior chamber depth from two-dimensional anterior segment photographs using deep learning.

BMC ophthalmology
BACKGROUND: The purpose of this study was to implement and evaluate a deep learning (DL) approach for automatically detecting shallow anterior chamber depth (ACD) from two-dimensional (2D) overview anterior segment photographs.

Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data.

BMC bioinformatics
BACKGROUND: With the rapid advancement of genomic sequencing techniques, massive production of gene expression data is becoming possible, which prompts the development of precision medicine. Deep learning is a promising approach for phenotype predict...

Neglected physical human-robot interaction may explain variable outcomes in gait neurorehabilitation research.

Science robotics
During gait neurorehabilitation, many factors influence the quality of gait patterns, particularly the chosen body-weight support (BWS) device. Consequently, robotic BWS devices play a key role in gait rehabilitation of people with neurological disor...

The relevance of signal timing in human-robot collaborative manipulation.

Science robotics
To achieve a seamless human-robot collaboration, it is crucial that robots express their intentions without perturbating or interrupting the task that a human partner is performing at that moment. Although it has not received much attention so far, t...

Persuasive robots should avoid authority: The effects of formal and real authority on persuasion in human-robot interaction.

Science robotics
Social robots must take on many roles when interacting with people in everyday settings, some of which may be authoritative, such as a nurse, teacher, or guard. It is important to investigate whether and how authoritative robots can influence people ...

Learning, visualizing and exploring 16S rRNA structure using an attention-based deep neural network.

PLoS computational biology
Recurrent neural networks with memory and attention mechanisms are widely used in natural language processing because they can capture short and long term sequential information for diverse tasks. We propose an integrated deep learning model for micr...

Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment.

PLoS computational biology
HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting genetically similar genotyped viral sequences in the network implying epidemiological transmissions. This tech...

Principles for Real-World Implementation of Bedside Predictive Analytics Monitoring.

Applied clinical informatics
A new development in the practice of medicine is Artificial Intelligence-based predictive analytics that forewarn clinicians of future deterioration of their patients. This proactive opportunity, though, is different from the reactive stance that cli...

Machine learning methods for automated classification of tumors with papillary thyroid carcinoma-like nuclei: A quantitative analysis.

PloS one
When approaching thyroid gland tumor classification, the differentiation between samples with and without "papillary thyroid carcinoma-like" nuclei is a daunting task with high inter-observer variability among pathologists. Thus, there is increasing ...

Implementation of artificial intelligence algorithms for melanoma screening in a primary care setting.

PloS one
Skin cancer is currently the most common type of cancer among Caucasians. The increase in life expectancy, along with new diagnostic tools and treatments for skin cancer, has resulted in unprecedented changes in patient care and has generated a great...