AIMC Topic: Young Adult

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Major depression disorder diagnosis and analysis based on structural magnetic resonance imaging and deep learning.

Journal of integrative neuroscience
Major depression disorder is one of the diseases with the highest rate of disability and morbidity and is associated with numerous structural and functional differences in neural systems. However, it is difficult to analyze digital medical imaging da...

Improvement of depiction of the intracranial arteries on brain CT angiography using deep learning reconstruction.

Journal of integrative neuroscience
To evaluate the ability of a commercialized deep learning reconstruction technique to depict intracranial vessels on the brain computed tomography angiography and compare the image quality with filtered-back-projection and hybrid iterative reconstruc...

[The accuracy and influencing factors of sleep staging based on single-channel EEG via a deep neural network].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
To investigate theaccuracy of artificial intelligence sleep staging model in patients with habitual snoring and obstructive sleep apnea hypopnea syndrome (OSAHS) based on single-channel EEG collected from different locations of the head. The clinic...

The potential of using artificial intelligence to improve skin cancer diagnoses in Hawai'i's multiethnic population.

Melanoma research
Skin cancer remains the most commonly diagnosed cancer in the USA with more than 1 million new cases each year. Melanomas account for about 1% of all skin cancers and most skin cancer deaths. Multiethnic individuals whose skin is pigmented underestim...

Individual versus Group Calibration of Machine Learning Models for Physical Activity Assessment Using Body-Worn Accelerometers.

Medicine and science in sports and exercise
PURPOSE: We sought to determine if individually calibrated machine learning models yielded higher accuracy than a group calibration approach for physical activity intensity assessment.

Predicting Sex-Specific Nonfatal Suicide Attempt Risk Using Machine Learning and Data From Danish National Registries.

American journal of epidemiology
Suicide attempts are a leading cause of injury globally. Accurate prediction of suicide attempts might offer opportunities for prevention. This case-cohort study used machine learning to examine sex-specific risk profiles for suicide attempts in Dani...

Machine Learning Model for Predicting CVD Risk on NHANES Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cardiovascular disease (CVD) is a major health problem throughout the world. It is the leading cause of morbidity and mortality and also causes considerable economic burden to society. The early symptoms related to previous observations and abnormal ...

Exploration of Machine Learning and Statistical Techniques in Development of a Low-Cost Screening Method Featuring the Global Diet Quality Score for Detecting Prediabetes in Rural India.

The Journal of nutrition
BACKGROUND: The prevalence of type 2 diabetes has increased substantially in India over the past 3 decades. Undiagnosed diabetes presents a public health challenge, especially in rural areas, where access to laboratory testing for diagnosis may not b...