AIMC Topic: Humans

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Toward a novel soft robotic system for minimally invasive interventions.

International journal of computer assisted radiology and surgery
PURPOSE: During minimally invasive surgery, surgeons maneuver tools through complex anatomies, which is difficult without the ability to control the position of the tools inside the body. A potential solution for a substantial portion of these proced...

Deep learning-based motion correction algorithm for coronary CT angiography: Lowering the phase requirement for morphological and functional evaluation.

Journal of applied clinical medical physics
PURPOSE: To investigate the performance of a deep learning-based motion correction algorithm (MCA) at various cardiac phases of coronary computed tomography angiography (CCTA), and determine the extent to which it may allow for reliable morphological...

Functional Outcome Prediction in Acute Ischemic Stroke Using a Fused Imaging and Clinical Deep Learning Model.

Stroke
BACKGROUND: Predicting long-term clinical outcome based on the early acute ischemic stroke information is valuable for prognostication, resource management, clinical trials, and patient expectations. Current methods require subjective decisions about...

The role of artificial intelligence in the future of urogynecology.

International urogynecology journal
Artificial intelligence (AI) in medicine is a rapidly growing field aimed at using machine learning models to improve health outcomes and patient experiences. Many new platforms have become accessible and therefore it seems inevitable that we conside...

Packets-to-Prediction: An Unobtrusive Mechanism for Identifying Coarse-Grained Sleep Patterns with WiFi MAC Layer Traffic.

Sensors (Basel, Switzerland)
A good night's sleep is of the utmost importance for the seamless execution of our cognitive capabilities. Unfortunately, the research shows that one-third of the US adult population is severely sleep deprived. With college students as our focused gr...

Psychometric evaluation of Persian version of medical artificial intelligence readiness scale for medical students.

BMC medical education
BACKGROUND: Artificial intelligence's advancement in medicine and its worldwide implementation will be one of the main elements of medical education in the coming years. This study aimed to translate and psychometric evaluation of the Persian version...

Comparing the performance of machine learning and conventional models for predicting atherosclerotic cardiovascular disease in a general Chinese population.

BMC medical informatics and decision making
BACKGROUND: Accurately predicting the risk of atherosclerotic cardiovascular disease (ASCVD) is crucial for implementing individualized prevention strategies and improving patient outcomes. Our objective is to develop machine learning (ML)-based mode...

Artificial intelligence for the diagnosis of clinically significant prostate cancer based on multimodal data: a multicenter study.

BMC medicine
BACKGROUND: The introduction of multiparameter MRI and novel biomarkers has greatly improved the prediction of clinically significant prostate cancer (csPCa). However, decision-making regarding prostate biopsy and prebiopsy examinations is still diff...

A novel machine learning model for predicting clinical pregnancy after laparoscopic tubal anastomosis.

BMC pregnancy and childbirth
BACKGROUND: Laparoscopic tubal anastomosis (LTA) is a treatment for women who require reproduction after ligation, and there are no reliable prediction models or clinically useful tools for predicting clinical pregnancy in women who receive this proc...

A nystagmus extraction system using artificial intelligence for video-nystagmography.

Scientific reports
Benign paroxysmal positional vertigo (BPPV), the most common vestibular disorder, is diagnosed by an examiner changing the posture of the examinee and inducing nystagmus. Among the diagnostic methods used to observe nystagmus, video-nystagmography ha...