AI Medical Compendium Topic:
Case-Control Studies

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Using Wearable Sensors and Machine Learning Models to Separate Functional Upper Extremity Use From Walking-Associated Arm Movements.

Archives of physical medicine and rehabilitation
OBJECTIVE: To improve measurement of upper extremity (UE) use in the community by evaluating the feasibility of using body-worn sensor data and machine learning models to distinguish productive prehensile and bimanual UE activity use from extraneous ...

Beating Heart Minimally Invasive Mitral Valve Surgery in Patients With Patent Coronary Bypass Grafts.

The Canadian journal of cardiology
BACKGROUND: Redo mitral valve surgery in patients with patent coronary bypass grafts carries a risk of graft injury and postoperative bleeding. We compare early results of reoperative minimally invasive on-pump beating heart mitral valve surgery (OPB...

Machine Learning of DTI Structural Brain Connectomes for Lateralization of Temporal Lobe Epilepsy.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
BACKGROUND AND PURPOSE: We analyzed the ability of a machine learning approach that uses diffusion tensor imaging (DTI) structural connectomes to determine lateralization of epileptogenicity in temporal lobe epilepsy (TLE).

Scalable gastroscopic video summarization via similar-inhibition dictionary selection.

Artificial intelligence in medicine
OBJECTIVE: This paper aims at developing an automated gastroscopic video summarization algorithm to assist clinicians to more effectively go through the abnormal contents of the video.

Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.

Psychiatry research
Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to ad...

Identifying neuroanatomical signatures of anorexia nervosa: a multivariate machine learning approach.

Psychological medicine
BACKGROUND: There are currently no neuroanatomical biomarkers of anorexia nervosa (AN) available to make clinical inferences at an individual subject level. We present results of a multivariate machine learning (ML) approach utilizing structural neur...