AIMC Topic: Female

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Artificial intelligence-enhanced electrocardiogram diastolic function grade predicts post-septal myectomy mortality in hypertrophic cardiomyopathy.

The Journal of thoracic and cardiovascular surgery
BACKGROUNDS: Diastolic dysfunction is an important pathophysiologic feature of hypertrophic cardiomyopathy that is often challenging to determine noninvasively. This study investigated whether a novel artificial intelligence-enabled electrocardiograp...

Integrating Motor Unit Activity With Deep Learning for Real-Time, Simultaneous and Proportional Wrist Angle and Grasp Force Estimation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Myoelectric prostheses offer great promise in enabling amputees to perform daily activities independently. However, existing neural interfaces generally cannot simultaneously and proportionally decode kinematics and kinetics in real time, ...

Real-world effectiveness of cariprazine in major depressive disorder and bipolar I disorder in the United States.

Journal of medical economics
AIMS: The efficacy of cariprazine for major depressive disorder (MDD) (adjunctive therapy) and bipolar I (BP-I) depression has been demonstrated in clinical trials. This study evaluated the real-world effectiveness of cariprazine in reducing depressi...

Mapping trait justice sensitivity in the Brain: Whole-brain resting-state functional connectivity as a predictor of other-oriented not self-oriented justice sensitivity.

Cognitive, affective & behavioral neuroscience
Justice sensitivity (JS) reflects personal concern and commitment to the principle of justice, showing considerable heterogeneity among the general population. Despite a growing interest in the behavioral characteristics of JS over the past decades, ...

Ultrasound image-based contrastive fusion non-invasive liver fibrosis staging algorithm.

Abdominal radiology (New York)
OBJECTIVE: The diagnosis of liver fibrosis is usually based on histopathological examination of liver puncture specimens. Although liver puncture is accurate, it has invasive risks and high economic costs, which are difficult for some patients to acc...

Hierarchical Transformer Fusion of Gaze Attention and Muscle Activity for Forearm Movement Estimation.

IEEE transactions on bio-medical engineering
Tracking forearm movement via measured physiological signals is crucial for understanding human motor control mechanism. Current methods mainly use muscle-derived signals to predict arm movements while often overlooking the potential role of gaze att...

Rate- and Patient-Specific Risk Factors for Periprosthetic Acetabular Fractures During Primary Total Hip Arthroplasty Using a Press-Fit Cup.

The Journal of arthroplasty
BACKGROUND: Periprosthetic acetabular fractures following primary total hip arthroplasty (THA) using a cementless acetabular component range from occult to severe fractures. The aims of this study were to evaluate the perioperative periprosthetic ace...

ECG-SMART-NET: A Deep Learning Architecture for Precise ECG Diagnosis of Occlusion Myocardial Infarction.

IEEE transactions on bio-medical engineering
OBJECTIVE: In this paper we develop and evaluate ECG-SMART-NET for occlusion myocardial infarction (OMI) identification. OMI is a severe form of heart attack characterized by complete blockage of one or more coronary arteries requiring immediate refe...

Preoperative risk assessment of invasive endometrial cancer using MRI-based radiomics: a systematic review and meta-analysis.

Abdominal radiology (New York)
OBJECTIVE: Image-derived machine learning (ML) is a robust and growing field in diagnostic imaging systems for both clinicians and radiologists. Accurate preoperative radiological evaluation of the invasive ability of endometrial cancer (EC) can incr...

End-to-end prognostication in pancreatic cancer by multimodal deep learning: a retrospective, multicenter study.

European radiology
OBJECTIVES: Pancreatic cancer treatment plans involving surgery and/or chemotherapy are highly dependent on disease stage. However, current staging systems are ineffective and poorly correlated with survival outcomes. We investigate how artificial in...