AIMC Topic: Humans

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Anatomical classification of upper gastrointestinal organs under various image capture conditions using AlexNet.

Computers in biology and medicine
BACKGROUND: Machine learning has led to several endoscopic studies about the automated localization of digestive lesions and prediction of cancer invasion depth. Training and validation dataset collection are required for a disease in each digestive ...

Reliability and accuracy of EEG interpretation for estimating age in preterm infants.

Annals of clinical and translational neurology
OBJECTIVES: To determine the accuracy of, and agreement among, EEG and aEEG readers' estimation of maturity and a novel computational measure of functional brain age (FBA) in preterm infants.

Transduction Mechanisms, Micro-Structuring Techniques, and Applications of Electronic Skin Pressure Sensors: A Review of Recent Advances.

Sensors (Basel, Switzerland)
Electronic skin (e-skin), which is an electronic surrogate of human skin, aims to recreate the multifunctionality of skin by using sensing units to detect multiple stimuli, while keeping key features of skin such as low thickness, stretchability, fle...

AutoAudio: Deep Learning for Automatic Audiogram Interpretation.

Journal of medical systems
Hearing loss is the leading human sensory system loss, and one of the leading causes for years lived with disability with significant effects on quality of life, social isolation, and overall health. Coupled with a forecast of increased hearing loss ...

Machine learning-based prediction of acute coronary syndrome using only the pre-hospital 12-lead electrocardiogram.

Nature communications
Prompt identification of acute coronary syndrome is a challenge in clinical practice. The 12-lead electrocardiogram (ECG) is readily available during initial patient evaluation, but current rule-based interpretation approaches lack sufficient accurac...

Predicting Absenteeism and Temporary Disability Using Machine Learning: a Systematic Review and Analysis.

Journal of medical systems
The main objective of this paper is to present a systematic analysis and review of the state of the art regarding the prediction of absenteeism and temporary incapacity using machine learning techniques. Moreover, the main contribution of this resear...

Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study.

JMIR mHealth and uHealth
BACKGROUND: Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing ...

Deep learning-based image reconstruction and motion estimation from undersampled radial k-space for real-time MRI-guided radiotherapy.

Physics in medicine and biology
To enable magnetic resonance imaging (MRI)-guided radiotherapy with real-time adaptation, motion must be quickly estimated with low latency. The motion estimate is used to adapt the radiation beam to the current anatomy, yielding a more conformal dos...