AIMC Topic: Humans

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Automatic craniomaxillofacial landmarks detection in CT images of individuals with dentomaxillofacial deformities by a two-stage deep learning model.

BMC oral health
BACKGROUND: Accurate cephalometric analysis plays a vital role in the diagnosis and subsequent surgical planning in orthognathic and orthodontics treatment. However, manual digitization of anatomical landmarks in computed tomography (CT) is subject t...

Prediction of therapeutic intensity level from automatic multiclass segmentation of traumatic brain injury lesions on CT-scans.

Scientific reports
The prediction of the therapeutic intensity level (TIL) for severe traumatic brain injury (TBI) patients at the early phase of intensive care unit (ICU) remains challenging. Computed tomography images are still manually quantified and then underexplo...

Applications of Artificial Intelligence in Health Care Delivery.

Journal of medical systems
Health care costs now comprise nearly one-fifth of the United States' gross domestic product, with the last 25 years marked by rising administrative costs, a lack of labor productivity growth, and rising patient and physician dissatisfaction. Policy ...

Humans are biocultural, science should be too.

Science (New York, N.Y.)
COVID-19 is restructuring societies. Loneliness is a global health threat. Large language models are outputting biased health care information, and human-artificial intelligence (AI) interfaces are reshaping how we live. For most humans, technology, ...

Experimental validation of immunogenic SARS-CoV-2 T cell epitopes identified by artificial intelligence.

Frontiers in immunology
During the COVID-19 pandemic we utilized an AI-driven T cell epitope prediction tool, the NEC Immune Profiler (NIP) to scrutinize and predict regions of T cell immunogenicity (hotspots) from the entire SARS-CoV-2 viral proteome. These immunogenic reg...

Improving the acceptability of social robots: Make them look different from humans.

PloS one
The social robots market will grow considerably in the coming years. What the arrival of these new kind of social agents means for society, however, is largely unknown. Existing cases of robot abuse point to risks of introducing such artificial socia...

Deep learning framework for epidemiological forecasting: A study on COVID-19 cases and deaths in the Amazon state of ParĂ¡, Brazil.

PloS one
Modeling time series has been a particularly challenging aspect due to the need for constant adjustments in a rapidly changing environment, data uncertainty, dependencies between variables, volatile fluctuations, and the need to identify ideal hyperp...

Deep Learning-based Assessment of Facial Asymmetry Using U-Net Deep Convolutional Neural Network Algorithm.

The Journal of craniofacial surgery
OBJECTIVES: This study aimed to evaluate the diagnostic performance of a deep convolutional neural network (DCNN)-based computer-assisted diagnosis (CAD) system to detect facial asymmetry on posteroanterior (PA) cephalograms and compare the results o...

Classification of rib fracture types from postmortem computed tomography images using deep learning.

Forensic science, medicine, and pathology
Human or time resources can sometimes fall short in medical image diagnostics, and analyzing images in full detail can be a challenging task. With recent advances in artificial intelligence, an increasing number of systems have been developed to assi...