Arrhythmia constitutes a problem with the rate or rhythm of the heartbeat, and an early diagnosis is essential for the timely inception of successful treatment. We have jointly optimized the entire multi-stage arrhythmia classification scheme based on 12-lead surface ECGs that attains the accuracy performance level of professional cardiologists. The new approach is comprised of a three-step noise reduction stage, a novel feature extraction method and an optimal classification model with finely tuned hyperparameters. We carried out an exhaustive study comparing thousands of competing classification algorithms that were trained on our proprietary, large and expertly labeled dataset consisting of 12-lead ECGs from 40,258 patients with four arrhythmia classes: atrial fibrillation, general supraventricular tachycardia, sinus bradycardia and sinus rhythm including sinus irregularity rhythm. Our results show that the optimal approach consisted of Low Band Pass filter, Robust LOESS, Non Local Means smoothing, a proprietary feature extraction method based on percentiles of the empirical distribution of ratios of interval lengths and magnitudes of peaks and valleys, and Extreme Gradient Boosting Tree classifier, achieved an F 1 -Score of 0.988 on patients without additional cardiac conditions. The same noise reduction and feature extraction methods combined with Gradient Boosting Tree classifier achieved an F 1 -Score of 0.97 on patients with additional cardiac conditions. Our method achieved the highest classification accuracy (average 10-fold cross-validation F 1 -Score of 0.992) using an external validation data, MIT-BIH arrhythmia database. The proposed optimal multi-stage arrhythmia classification approach can dramatically benefit automatic ECG data analysis by providing cardiologist level accuracy and robust compatibility with various ECG data sources.ECGs represent the filtered electrical activity generated by the heart. An ECG from lead II presents a normal heartbeat under sinus rhythm that has a characteristic shape with three features, a P-wave presenting the atrial depolarization process, a QRS complex denoting the ventricular depolarization process, and a T-wave representing the ventricular repolarization. The normal feature sequence of the cardiac cycle is P-wave, QRS complex, and T-wave with sections between them called segments. Three such major segments are the PR, ST, and TP segments. Important periods within and between ECG waves are the PR, QT, and RR intervals.Damage to the heart muscle or nerves can change the electrical activity of the heart and induce a corresponding change in the shape of the ECGs. Thus, ECG is a major clinical diagnostic tool for various heart abnormalities. Arrhythmias are a family of conditions characterized by aberrations from the normal rate or rhythm of the heartbeats. There are several dozen classes of arrhythmia with various distinct manifestations, excessively slow or fast heartbeats such as sinus bradycardia and atrial tachycardia, irregular rhythm with missing or distorte...

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The advent of more advanced 3D image processing, reconstruction, and a variety of three-dimensional (3D) printing technologies using different materials has made rapid and fairly affordable anatomically accurate models much more achievable. These models show great promise in facilitating procedural and surgical planning for complex congenital and structural heart disease. Refinements in 3D printing technology lend itself to advanced applications in the fields of bio-printing, hemodynamic modeling, and implantable devices. As a novel technology with a large variability in software, processing tools and printing techniques, there is not a standardized method by which a clinician can go from an imaging data-set to a complete model. Furthermore, anatomy of interest and how the model is used can determine the most appropriate technology. In this over-view we discuss, from the standpoint of a clinical professional, image acquisition, processing, and segmentation by which a printable file is created. We then review the various printing technologies, advantages and disadvantages when printing the completed model file, and describe clinical scenarios where 3D printing can be utilized to address therapeutic challenges.

In this study, we report significant associations between BKPyV reactivation following allogeneic HSCT and suppressed immune variables. In addition, this study provides valuable information on the immune status of HSCT recipients as a predictor of BKPyV infections that may in turn help us formulate plans for more effective prevention and treatment of this infection.