Deep learning for the classification of atrial fibrillation using wavelet transform-based visual images.

Background: As the incidence and prevalence of Atrial Fibrillation (AF) proliferate worldwide, the condition has become the epicenter of a plethora of ECG diagnostic research. In recent diagnostic methodologies, Morse Continuous Wavelet Transform (MsCWT) is a feature extraction technique utilized to draw out distinctive attributes of ECG signals. In our study, we explore the employment of MsCWT in the classification of AF with ECG signals in a continuum.

Early effect of standalone oblique lateral interbody fusion vs. combined with lateral screw fixation of the vertebral body on single-level lumbar degenerative disc disease: A pilot study.

Background: For the treatment of single-level lumbar degenerative disc disease (DDD), oblique lateral interbody fusion (OLIF) has clinical advantages. Whether internal fixation needs to be combined for treatment has been the subject of debate.

Objective: To compare the early clinical effects of standalone oblique lateral interbody fusion (S-OLIF) versus OLIF combined with lateral screw fixation of the vertebral body (F-OLIF) on single-level lumbar DDD.

Generative adversarial network-based deep learning approach in classification of retinal conditions with optical coherence tomography images.

Purpose: To determine whether a deep learning approach using generative adversarial networks (GANs) is beneficial for the classification of retinal conditions with Optical coherence tomography (OCT) images.

Methods: Our study utilized 84,452 retinal OCT images obtained from a publicly available dataset (Kermany Dataset). Employing GAN, synthetic OCT images are produced to balance classes of retinal disorders.

Chronic Inflammation Pathway NF-κB Cooperates with Epigenetic Reprogramming to Drive the Malignant Progression of Glioblastoma.

Without an effective strategy for targeted therapy, glioblastoma is still incurable with a median survival of only 15 months. Both chronic inflammation and epigenetic reprogramming are hallmarks of cancer. However, the mechanisms and consequences of their cooperation in glioblastoma remain unknown.

Using machine learning to determine the correlation between physiological and environmental parameters and the induction of acute mountain sickness.

Background: Recent studies on acute mountain sickness (AMS) have used fixed-location and fixed-time measurements of environmental and physiological variable to determine the influence of AMS-associated factors in the human body. This study aims to measure, in real time, environmental conditions and physiological variables of participants in high-altitude regions to develop an AMS risk evaluation model to forecast prospective development of AMS so its onset can be prevented.

Results: Thirty-two participants were recruited, namely 25 men and 7 women, and they hiked from Cuifeng Mountain Forest Park parking lot (altitude: 2300 m) to Wuling (altitude: 3275 m).

Research progress on negative pressure wound therapy with instillation in the treatment of orthopaedic wounds.

Negative pressure wound therapy with instillation (NPWTi) has the dual function of negative pressure sealing drainage and irrigation, which overcomes the disadvantages of NPWT, such as tube obstruction, inability to apply topical medicine, and poor anti-infection ability. NPWTi has been researched extensively and widely used in various types of wounds, and certain effects have been achieved. A series of parameters for NPWTi have not been unified at present, including the flushing fluid option, flushing mode, and treatment period.

General deep learning model for detecting diabetic retinopathy.

Background: Doctors can detect symptoms of diabetic retinopathy (DR) early by using retinal ophthalmoscopy, and they can improve diagnostic efficiency with the assistance of deep learning to select treatments and support personnel workflow. Conventionally, most deep learning methods for DR diagnosis categorize retinal ophthalmoscopy images into training and validation data sets according to the 80/20 rule, and they use the synthetic minority oversampling technique (SMOTE) in data processing (e.g.

Circular RNA CDR1as disrupts the p53/MDM2 complex to inhibit Gliomagenesis.

Background: Inactivation of the tumor suppressor p53 is critical for pathogenesis of glioma, in particular glioblastoma multiforme (GBM). MDM2, the main negative regulator of p53, binds to and forms a stable complex with p53 to regulate its activity. Hitherto, it is unclear whether the stability of the p53/MDM2 complex is affected by lncRNAs, in particular circular RNAs that are usually abundant and conserved, and frequently implicated in different oncogenic processes.

Systematic node management mechanism using ZigBee-based real-time vital sign information monitoring system to manage large numbers of patients.

Background: Local hospitals must deal with large numbers of patients during mass casualty incidents, and the wireless sensor networks (WSNs) can help in these situations by monitoring vital signs. Conventional ZigBee nodes can obtain the ID of a device by assigning a unique 16-bit short address or by burning firmware into an IC. These methods tend to complicate node management and lack portability.