AIMC Topic: Young Adult

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COVID-19 Patient Health Prediction Using Boosted Random Forest Algorithm.

Frontiers in public health
Integration of artificial intelligence (AI) techniques in wireless infrastructure, real-time collection, and processing of end-user devices is now in high demand. It is now superlative to use AI to detect and predict pandemics of a colossal nature. T...

Brain-optimized extraction of complex sound features that drive continuous auditory perception.

PLoS computational biology
Understanding how the human brain processes auditory input remains a challenge. Traditionally, a distinction between lower- and higher-level sound features is made, but their definition depends on a specific theoretical framework and might not match ...

Trust in artificial intelligence for medical diagnoses.

Progress in brain research
We present two online experiments investigating trust in artificial intelligence (AI) as a primary and secondary medical diagnosis tool and one experiment testing two methods to increase trust in AI. Participants in Experiment 1 read hypothetical sce...

Evaluation of marker selection methods and statistical models for chronological age prediction based on DNA methylation.

Legal medicine (Tokyo, Japan)
In forensic investigation, retrieving biological information from DNA evidence is a promising field of interest. One of the applications is on the estimation of the age of the donor based on DNA methylation. A large number of studies focused on age p...

Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients.

The British journal of ophthalmology
BACKGROUND/AIMS: Human grading of digital images from diabetic retinopathy (DR) screening programmes represents a significant challenge, due to the increasing prevalence of diabetes. We evaluate the performance of an automated artificial intelligence...

Machine learning prediction of combat basic training injury from 3D body shape images.

PloS one
INTRODUCTION: Athletes and military personnel are both at risk of disabling injuries due to extreme physical activity. A method to predict which individuals might be more susceptible to injury would be valuable, especially in the military where basic...

A machine learning-based prognostic predictor for stage III colon cancer.

Scientific reports
Limited biomarkers have been identified as prognostic predictors for stage III colon cancer. To combat this shortfall, we developed a computer-aided approach which combing convolutional neural network with machine classifier to predict the prognosis ...

Utilization of machine learning to test the impact of cognitive processing and emotion recognition on the development of PTSD following trauma exposure.

BMC psychiatry
BACKGROUND: Though lifetime exposure to traumatic events is significant, only a minority of individuals develops symptoms of posttraumatic stress disorder (PTSD). Post-trauma alterations in neurocognitive and affective functioning are likely to refle...