AIMC Topic: Humans

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Deep-Learning Models for the Echocardiographic Assessment of Diastolic Dysfunction.

JACC. Cardiovascular imaging
OBJECTIVES: The authors explored a deep neural network (DeepNN) model that integrates multidimensional echocardiographic data to identify distinct patient subgroups with heart failure with preserved ejection fraction (HFpEF).

Is there a difference between navigated and non-navigated robot cohorts in robot-assisted spine surgery? A multicenter, propensity-matched analysis of 2,800 screws and 372 patients.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Robot-assisted spine surgery continues to rapidly develop as evidenced by the growing literature in recent years. In addition to demonstrating excellent pedicle screw accuracy, early studies have explored the impact of robot-assis...

Feasibility of a generalized convolutional neural network for automated identification of vertebral compression fractures: The Manitoba Bone Mineral Density Registry.

Bone
BACKGROUND: Vertebral fracture assessment (VFA) images are acquired in dual-energy (DE) or single-energy (SE) scan modes. Automated identification of vertebral compression fractures, from VFA images acquired using GE Healthcare scanners in DE mode, h...

Machine Learning Analysis of MicroRNA Expression Data Reveals Novel Diagnostic Biomarker for Ischemic Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Ischemic stroke (IS) is one of the leading causes of morbidity and mortality worldwide. Circulating microRNAs have a potential as minimally invasive biomarkers for disease prediction, diagnosis, and prognosis. In this study, we sought to ...

Impact of the Implementation of the EAU Guidelines Recommendation on Reporting and Grading of Complications in Patients Undergoing Robot-assisted Radical Cystectomy: A Systematic Review.

European urology
In 2012, the European Association of Urology (EAU) Ad Hoc Panel proposed a standardised methodology on reporting and grading complications after urological surgical procedures. The aim of the current study was to assess the impact of this implementat...

Machine learning directed drug formulation development.

Advanced drug delivery reviews
Machine learning (ML) has enabled ground-breaking advances in the healthcare and pharmaceutical sectors, from improvements in cancer diagnosis, to the identification of novel drugs and drug targets as well as protein structure prediction. Drug formul...

Exploration of machine learning techniques to examine the journey to neuroendocrine tumor diagnosis with real-world data.

Future oncology (London, England)
Machine learning reveals pathways to neuroendocrine tumor (NET) diagnosis. Patients with NET and age-/gender-matched non-NET controls were retrospectively selected from MarketScan claims. Predictors (e.g., procedures, symptoms, conditions for which...

A real-time anatomy ıdentification via tool based on artificial ıntelligence for ultrasound-guided peripheral nerve block procedures: an accuracy study.

Journal of anesthesia
We aimed to assess the accuracy of an artificial intelligence (AI)-based real-time anatomy identification software specifically developed to ease image interpretation intended for ultrasound-guided peripheral nerve block (UGPNB). Forty healthy partic...