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COVID-19 has resulted in a significant global impact on health, the economy, education, and daily life. The disease can range from mild to severe, with individuals over 65 or those with underlying medical conditions being more susceptible to severe illness. Early testing and isolation are vital due to the virus’s variable incubation period. Chest radiographs (CXR) have gained importance as a diagnostic tool due to their efficiency and reduced radiation exposure compared to CT scans. However, the sensitivity of CXR in detecting COVID-19 may be lower. This paper introduces a deep learning framework for accurate COVID-19 classification and severity prediction using CXR images. U-Net is used for lung segmentation, achieving a precision of 0.9924. Classification is performed using a Convulation-capsule network, with high true positive rates of 86% for COVID-19, 93% for pneumonia, and 85% for normal cases. Severity assessment employs ResNet50, VGG-16, and DenseNet201, with DenseNet201 showing superior accuracy. Empirical results, validated with 95% confidence intervals, confirm the framework’s reliability and robustness. This integration of advanced deep learning techniques with radiological imaging enhances early detection and severity assessment, improving patient management and resource allocation in clinical settings. [ABSTRACT FROM AUTHOR]

Intraday trading is popular among traders due to its ability to leverage price fluctuations in a short timeframe. For traders, real-time price predictions for the next few minutes can be beneficial for making strategies. Real-time prediction is challenging due to the stock market's non-stationary, complex, noisy, chaotic, dynamic, volatile, and non-parametric nature. Machine learning models are considered effective for stock forecasting, yet, their hyperparameters need tuning with the latest market data to incorporate the market's complexities. Usually, models are trained and tested in batches, which smooths the correction process and speeds up the learning. When making intraday stock predictions, the models should forecast for each instance in contrast to the whole batch and learn simultaneously to ensure high accuracy. In this paper, we propose a strategy based on two different learning approaches: incremental learning and Offline–Online learning, to forecast the stock price using the real-time stream of the live market. In incremental learning, the model is updated continuously upon receiving the stock's next instance from the live-stream, while in Offline-Online learning, the model is retrained after each trading session to make sure it incorporates the latest data complexities. These methods were applied to univariate time-series (established from historical stock price) and multivariate time-series (considering historical stock price as well as technical indicators). Extensive experiments were performed on the eight most liquid stocks listed on the American NASDAQ and Indian NSE stock exchanges, respectively. The Offline–Online models outperformed incremental models in terms of low forecasting error. [ABSTRACT FROM AUTHOR]

Chiari malformation (CM) is a group of complex deformities of the posterior fossa and hindbrain, of which CMIII is the rarest. We report a term neonate, with an antenatal diagnosis of occipital encephalocele, who underwent resection of the encephalocele and ligation of vessels, with repair of a large scalp defect and dural reconstruction on day 4 of life. The parents of the child had been counselled for a guarded and poor prognosis on initial diagnosis. The child has had a good postoperative course without complications but suffers from cortical visual impairment and global developmental delay. [ABSTRACT FROM AUTHOR]

Introduction: Chronic Low Back Pain (CLBP), a well-known public health burden which progressively increased with time and development of trigger points in Quadratus Lumborum (QL) is frequently the cause of CLBP. Extracorporeal Shockwave Therapy (ESWT) is an entirely novel and effective non invasive therapy for treating myofascial trigger points. Aim: There is no comprehensive analysis which assess the effect of ESWT on QL trigger points associated with CLBP. As a result, aim of this review is to outlined the existing evidence available. Materials and Methods: Electronic databases which include PubMed/Medline, Scopus, Physiotherapy Evidence Database (PEDro), and Cochrane were searched. Searches were limited to full-text english language and publication between Jan 2000 to Jan 2024. In addition, reference list of the retrieved articles was also explored. A total of 678 relevant articles which includes 142 participants were identified in which participants were included. After duplicates were removed, articles were assessed for eligibility criteria. Five (n=5) articles met all criteria and were included in the final data synthesis. Results: The results shows that patients treated with ESWT shows statistically significant improvement in pain (p<0.05) for Visual Analogue Scale (VAS). Also, some studies show statistically significant improvement (p<0.05) in ODI (Oswestry Disability Index) and SF-36 (Short Form Health survey). [ABSTRACT FROM AUTHOR]

A letter published in the Journal of Multidisciplinary Healthcare critiques a study titled "Effectiveness of Asthma Home Management Manual and Low-Cost Air Filter on Quality of Life Among Asthma Adults: A 3-Arm Randomized Controlled Trial." The letter raises several concerns about the study, including the use of keywords not aligned with Medical Subject Headings, the need to consider minimum values of outcome measures before enrolling participants, the importance of considering the duration of asthma, the lack of clarity in data analysis methods, and the absence of descriptions for within-group and between-group analyses. The author encourages the study authors to address these concerns to improve the clarity and quality of the findings. [Extracted from the article]

The objectives of this study were i) to measure a six-minute step test (6MST) in asymptomatic adults; ii) to determine the applicability of Arcuri et al.'s reference equation to Indian adults; iii) to develop a prediction equation for Indian adults. 110 adult males and females aged 18-40 years were recruited for this prospective crosssectional study conducted in India. Participants underwent 6MST. Applicability was assessed by comparing the findings of the 6MST with the values derived from Arcuri et al.'s predicted equations using the Bland-Altman plot. A multiple regression analysis was used to develop the prediction equation. The mean±SD six-minute step count was 159.42±17.60 steps and 150.78±14.39 steps in males and females respectively. The 6MST for males can be determined by males (steps)=204.371-1.521×age(years) and females (steps)=179.567-1.06×age (years). Arcuri et al.'s equation cannot be used to predict 6MST in Indian adults. Region-specific equations are useful to assess the values. [ABSTRACT FROM AUTHOR]

A recent study titled "Multi-Sensory Stimuli Improve Relaxation and Sleep Quality in Rotating Shift Workers: A Randomized Controlled Trial" suggests that multisensory stimuli can improve the quality of sleep and relaxation for rotating shift workers. However, the authors of a letter to the editor raise several concerns about the study. They note that the trial registration number was not provided, which goes against journal guidelines, and that the article's keywords do not match the journal's requirements. Additionally, they point out that there is insufficient information about sample size estimation, the age range of participants is not adequately justified, and the results section lacks information about the normality of the data. The authors respectfully request that these concerns be addressed to enhance the integrity and clarity of the published results. [Extracted from the article]

The article presents a case study of a 14-year-old female, with no significant past medical history, presented to the local emergency center with 3 days of abdominal pain, decreased oral intake, nausea, and multiple episodes of nonblood, nonbilious emesis. It notes that the presented case is the first report of acute pancreatitis in a pediatric patient after the Covid vaccine; and the 2 reported adult cases without known risk factors, the episodes of acute pancreatitis were uncomplicated.