AIMC Topic: Middle Aged

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Expert-level sleep staging using an electrocardiography-only feed-forward neural network.

Computers in biology and medicine
Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for providing valuable insights, diagnoses, and understanding of brain states. The current gold standard method for sleep stage classification is polysomno...

AI-enabled electrocardiography alert intervention and all-cause mortality: a pragmatic randomized clinical trial.

Nature medicine
The early identification of vulnerable patients has the potential to improve outcomes but poses a substantial challenge in clinical practice. This study evaluated the ability of an artificial intelligence (AI)-enabled electrocardiogram (ECG) to ident...

Early prediction of sepsis-induced respiratory tract infection using a biomarker-based machine-learning algorithm.

Scandinavian journal of clinical and laboratory investigation
Early and differential diagnosis of sepsis is essential to avoid unnecessary antibiotic use and further reduce patient morbidity and mortality. Here, we aimed to identify predictors of sepsis and advance a machine-learning strategy to predict sepsis-...

Differentiating Epileptic and Psychogenic Non-Epileptic Seizures Using Machine Learning Analysis of EEG Plot Images.

Sensors (Basel, Switzerland)
The treatment of epilepsy, the second most common chronic neurological disorder, is often complicated by the failure of patients to respond to medication. Treatment failure with anti-seizure medications is often due to the presence of non-epileptic s...

Artificial intelligence assists identification and pathologic classification of glomerular lesions in patients with diabetic nephropathy.

Journal of translational medicine
BACKGROUND: Glomerular lesions are the main injuries of diabetic nephropathy (DN) and are used as a crucial index for pathologic classification. Manual quantification of these morphologic features currently used is semi-quantitative and time-consumin...

Preclinical identification of acute coronary syndrome without high sensitivity troponin assays using machine learning algorithms.

Scientific reports
Preclinical management of patients with acute chest pain and their identification as candidates for urgent coronary revascularization without the use of high sensitivity troponin essays remains a critical challenge in emergency medicine. We enrolled ...

A machine-learning method isolating changes in wrist kinematics that identify age-related changes in arm movement.

Scientific reports
Normal aging often results in an increase in physiological tremors and slowing of the movement of the hands, which can impair daily activities and quality of life. This study, using lightweight wearable non-invasive sensors, aimed to detect and ident...

Exploring inertial sensor-based balance biomarkers for early detection of mild cognitive impairment.

Scientific reports
Dementia is characterized by a progressive loss of cognitive abilities, and diagnosing its early stages Mild Cognitive Impairment (MCI), is difficult since it is a transitory state that is different from total cognitive collapse. Recent clinical rese...

Fully automated 3D machine learning model for HPV status characterization in oropharyngeal squamous cell carcinomas based on CT images.

American journal of otolaryngology
BACKGROUND: Human papillomavirus (HPV) status plays a major role in predicting oropharyngeal squamous cell carcinoma (OPSCC) survival. This study assesses the accuracy of a fully automated 3D convolutional neural network (CNN) in predicting HPV statu...