AIMC Topic: Humans

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Piloting an automated clinical trial eligibility surveillance and provider alert system based on artificial intelligence and standard data models.

BMC medical research methodology
BACKGROUND: To advance new therapies into clinical care, clinical trials must recruit enough participants. Yet, many trials fail to do so, leading to delays, early trial termination, and wasted resources. Under-enrolling trials make it impossible to ...

Simulating complex patient populations with hierarchical learning effects to support methods development for post-market surveillance.

BMC medical research methodology
BACKGROUND: Validating new algorithms, such as methods to disentangle intrinsic treatment risk from risk associated with experiential learning of novel treatments, often requires knowing the ground truth for data characteristics under investigation. ...

Stereology neuron counts correlate with deep learning estimates in the human hippocampal subregions.

Scientific reports
Hippocampal subregions differ in specialization and vulnerability to cell death. Neuron death and hippocampal atrophy have been a marker for the progression of Alzheimer's disease. Relatively few studies have examined neuronal loss in the human brain...

Prediction of Fishman's skeletal maturity indicators using artificial intelligence.

Scientific reports
The present study aimed to evaluate the performance of automated skeletal maturation assessment system for Fishman's skeletal maturity indicators (SMI) for the use in dental fields. Skeletal maturity is particularly important in orthodontics for the ...

Recurrent neural networks for time domain modelling of FTIR spectra: application to brain tumour detection.

The Analyst
Attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy alongside machine learning (ML) techniques is an emerging approach for the early detection of brain cancer in clinical practice. A crucial step in the acquisition of an...

Self-Supervised EEG Emotion Recognition Models Based on CNN.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Emotion plays crucial roles in human life. Recently, emotion classification from electroencephalogram (EEG) signal has attracted attention by researchers due to the rapid development of brain computer interface (BCI) techniques and machine learning a...

Metastable alpha-rich and beta-rich conformations of small Aβ42 peptide oligomers.

Proteins
Probing the structures of amyloid-β (Aβ) peptides in the early steps of aggregation is extremely difficult experimentally and computationally. Yet, this knowledge is extremely important as small oligomers are the most toxic species. Experiments and s...

An expert-based system to predict population survival rate from health data.

Conservation biology : the journal of the Society for Conservation Biology
Timely detection and understanding of causes for population decline are essential for effective wildlife management and conservation. Assessing trends in population size has been the standard approach, but we propose that monitoring population health...

A deep learning and docking simulation-based virtual screening strategy enables the rapid identification of HIF-1α pathway activators from a marine natural product database.

Journal of biomolecular structure & dynamics
Artificial Intelligence is hailed as a cutting-edge technology for accelerating drug discovery efforts, and our goal was to validate its potential in predicting pharmacological inhibitors of EGLN1 using a deep learning-based architecture, one of its ...

Blockchain technology and federated machine learning for collaborative initiatives in orthodontics and craniofacial health.

Orthodontics & craniofacial research
There is a paucity of largescale collaborative initiatives in orthodontics and craniofacial health. Such nationally representative projects would yield findings that are generalizable. The lack of large-scale collaborative initiatives in the field of...