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Total 162 results found since Jan 2013.

A review of machine learning techniques in photoplethysmography for the non-invasive cuff-less measurement of blood pressure
Publication date: April 2020Source: Biomedical Signal Processing and Control, Volume 58Author(s): C. El-Hajj, P.A. KyriacouAbstractHypertension or high blood pressure is a leading cause of death throughout the world and a critical factor for increasing the risk of serious diseases, including cardiovascular diseases such as stroke and heart failure. Blood pressure is a primary vital sign that must be monitored regularly for the early detection, prevention and treatment of cardiovascular diseases. Traditional blood pressure measurement techniques are either invasive or cuff-based, which are impractical, intermittent, and unc...
Source: Biomedical Signal Processing and Control - February 13, 2020 Category: Biomedical Science Source Type: research

Deep learning approach for diabetes prediction using PIMA Indian dataset
ConclusionThe outcome of the study confirms that DL provides the best results with the most promising extracted features. DL achieves the accuracy of 98.07% which can be used for further development of the automatic prognosis tool. The accuracy of the DL approach can further be enhanced by including the omics data for prediction of the onset of the disease.
Source: Journal of Diabetes and Metabolic Disorders - April 13, 2020 Category: Endocrinology Source Type: research

A stacked LSTM for atrial fibrillation prediction based on multivariate ECGs
AbstractAtrial fibrillation (AF) is an irregular and rapid heart rate that can increase the risk of various heart-related complications, such as the stroke and the heart failure. Electrocardiography (ECG) is widely used to monitor the health of heart disease patients. It can dramatically improve the health and the survival rate of heart disease patients by accurately predicting the AFs in an ECG. Most of the existing researches focus on the AF detection, but few of them explore the AF prediction. In this paper, we develop a recurrent neural network (RNN) composed of stacked LSTMs for AF prediction, which called SLAP. This ...
Source: Health Information Science and Systems - April 20, 2020 Category: Information Technology Source Type: research

Integrating the STOP-BANG score and clinical data to predict cardiovascular events after infarction: A machine learning study.
Abstract BACKGROUND: Obstructive sleep apnea (OSA) conveys worse clinical outcomes in coronary artery disease patients. The STOP-BANG score is a simple tool that evaluates the risk of OSA and can be added to the large number of clinical variables and scores obtained during the management of myocardial infarction (MI) patients. Currently, machine learning (ML) is able to select and integrate numerous variables to optimize prediction tasks. RESEARCH QUESTION: Can the integration of STOP-BANG score with clinical data and scores through ML better identify patients who suffered an in-hospital cardiovascular event ...
Source: Chest - April 24, 2020 Category: Respiratory Medicine Authors: Calvillo-Argüelles O, Sierra-Fernández CR, Padilla-Ibarra J, Rodriguez-Zanella H, Balderas-Muñoz K, Arias-Mendoza MA, Martínez-Sánchez C, Selmen-Chattaj S, Dominguez-Mendez BE, van der Harst P, Juarez-Orozco LE Tags: Chest Source Type: research

Biventricular imaging markers to predict outcomes in non ‐compaction cardiomyopathy: a machine learning study
ConclusionsOur findings show the importance of biventricular assessment to detect the severity of this cardiomyopathy and to plan for early clinical intervention. In addition, this study shows that even patients with normal LV function and negative late gadolinium enhancement had MACE. ML is a promising tool for analysing a large set of parameters to stratify and predict prognosis in LVNC patients.
Source: ESC Heart Failure - June 29, 2020 Category: Cardiology Authors: Camila Rocon, Mahdi Tabassian, Marcelo Dantas Tavares de Melo, Jose Arimateia Araujo Filho, Cesar Jos é Grupi, Jose Rodrigues Parga Filho, Edimar Alcides Bocchi, Jan D'hooge, Vera Maria Cury Salemi Tags: Original Research Article Source Type: research

What Are the Main Acyanotic Congenital Heart Diseases?
Discussion Congenital heart diseases (CHD) are malformations of the heart and great vessels. It occurs in about 5-8/1000 live births. Cyanotic congenital heart disease is often noted perinatally because of cyanosis, respiratory distress and/or poor feeding or other distress type problems. A review can be found here. Acyanotic congenital heart disease (ACHD) can present at birth but often is seen in older children or adults unless the lesions are severe, especially obstructive lesions. Severe lesions may also cause cyanosis and distress type problems in patients also. Shunting lesions cause problems by diverting blood flo...
Source: PediatricEducation.org - August 17, 2020 Category: Pediatrics Authors: Pediatric Education Tags: Uncategorized Source Type: news

COVID-19 Exposed the Faults in America ’s Elder Care System. This Is Our Best Shot to Fix Them
For the American public, one of the first signs of the COVID-19 pandemic to come was a tragedy at a nursing home near Seattle. On Feb. 29, 2020, officials from the U.S. Centers for Disease Control and Prevention (CDC) and Washington State announced the U.S. had its first outbreak of the novel coronavirus. Three people in the area had tested positive the day before; two of them were associated with Life Care Center of Kirkland, and officials expected more to follow soon. When asked what steps the nursing home could take to control the spread, Dr. Jeff Duchin, health officer for Seattle and King County, said he was working w...
Source: TIME: Health - June 15, 2021 Category: Consumer Health News Authors: Abigail Abrams Tags: Uncategorized Aging COVID-19 feature franchise Magazine TIME for Health Source Type: news

Electronic Medical Record Risk Modeling of Cardiovascular Outcomes Among Patients with Type 2 Diabetes
ConclusionsThe Ochsner model overestimated 5-year CHD risk, but had relatively higher calibration than the other models in CHD. Risk equations fitted for local populations improved cardiovascular risk stratification for patients with T2DM. Application of machine learning simplified the models compared to “generalized” risk equations.
Source: Diabetes Therapy - June 18, 2021 Category: Endocrinology Source Type: research

Sensors, Vol. 21, Pages 5302: Automatic Detection of Short-Term Atrial Fibrillation Segments Based on Frequency Slice Wavelet Transform and Machine Learning Techniques
uang Zhou Atrial fibrillation (AF) is the most frequently encountered cardiac arrhythmia and is often associated with other cardiovascular and cerebrovascular diseases, such as ischemic heart disease, chronic heart failure, and stroke. Automatic detection of AF by analyzing electrocardiogram (ECG) signals has an important application value. Using the contaminated and actual ECG signals, it is not enough to only analyze the atrial activity of disappeared P wave and appeared F wave in the TQ segment. Moreover, the best analysis method is to combine nonlinear features analyzing ventricular activity based on the detection ...
Source: Sensors - August 5, 2021 Category: Biotechnology Authors: Yaru Yue Chengdong Chen Pengkun Liu Ying Xing Xiaoguang Zhou Tags: Article Source Type: research

‘Rise of the machines’: the next frontier in individualized medicine
Artificial intelligence (AI) andin silico models, in conjunction with the rapid adoption of mobile health (mHealth) technologies such as smart wearables, have the potential to revolutionize the monitoring, screening, and treatment of cardiovascular disease patients. Broadly speaking, AI and machine learning (ML) are predominantly statistical methods —learning from patient data to predict outcomes, with often little to no mechanistic understanding of the underlying processes. On the other hand, the nascent but rapidly developing field ofin silico models are mechanistic models —they use the underlying physics/chemistry t...
Source: Cardiovascular Research - July 19, 2021 Category: Cardiology Source Type: research

Striving to Deliver Better Outcomes: Janssen to Showcase Commitment to Advancing Science for Genitourinary Cancers at AUA 2021
August 31, 2021 (RARITAN, N.J.) – The Janssen Pharmaceutical Companies of Johnson & Johnson announced today multiple company-sponsored presentations in prostate and bladder cancers will be highlighted at the virtual 2021 American Urological Association Annual Meeting (AUA 2021), September 10-13. “Janssen maintains a strong commitment to advancing innovation and new therapeutic options for patients with genitourinary malignancies. As the treatment of genitourinary cancers becomes more complex, we continue to work with urologists and their teams to improve outcomes for patients across the continuum of disease,” sai...
Source: Johnson and Johnson - August 31, 2021 Category: Pharmaceuticals Tags: Our Company Source Type: news

Janssen Announces U.S. FDA Approval of INVEGA HAFYERA ™(6-month paliperidone palmitate), First and Only Twice-Yearly Treatment for Adults with Schizophrenia
TITUSVILLE, N.J., Sept. 1, 2021 – The Janssen Pharmaceutical Companies of Johnson & Johnson today announced the U.S. Food and Drug Administration (FDA) has approved long-acting atypical antipsychotic INVEGA HAFYERA™ (6-month paliperidone palmitate), the first-and-only twice-yearly injectable for the treatment of schizophrenia in adults. Before transitioning to INVEGA HAFYERA™, patients must be adequately treated with INVEGA SUSTENNA® (1-month paliperidone palmitate) for at least four months, or INVEGA TRINZA® (3-month paliperidone palmitate) for at least one 3-month injection cycle.1 The FDA approval of INVEGA ...
Source: Johnson and Johnson - September 1, 2021 Category: Pharmaceuticals Tags: Innovation Source Type: news

Janssen Demonstrates Commitment to Advancing Science and Innovation in the Treatment of Solid Tumors at ESMO Annual Congress
September 8, 2021 (RARITAN, N.J.) – The Janssen Pharmaceutical Companies of Johnson & Johnson announced today that more than ten data presentations from its lung cancer, bladder cancer and prostate cancer portfolio and pipeline will be featured during the European Society for Medical Oncology (ESMO) Annual Congress 2021 virtual meeting, September 16–21. Further details about these data and the science Janssen is advancing will be made available throughout ESMO via the Janssen Oncology Virtual Newsroom.“With a diverse oncology portfolio and pipeline spanning bladder cancer, lung cancer and prostate cancer, Janssen...
Source: Johnson and Johnson - September 8, 2021 Category: Pharmaceuticals Tags: Innovation Source Type: news

ERLEADA ® (apalutamide) Oral Presentations Demonstrate Importance of Prostate Specific Antigen (PSA) as Key Efficacy Indicator and Show Strong Patient Adherence Rates
September 11, 2021 (RARITAN, N.J.) – The Janssen Pharmaceutical Companies of Johnson & Johnson today announced new data demonstrating robust prostate-specific antigen (PSA) response and strong adherence rates in patients with non-metastatic castration-resistant prostate cancer (nmCRPC) treated with ERLEADA® (apalutamide) in the real-world clinical setting. The strong PSA response was also seen in a separate post-hoc analysis that showed a correlation between rapid and deep PSA response and prolonged survival in both metastatic castration-sensitive prostate cancer (mCSPC) and nmCRPC. The post-hoc analysis also suppor...
Source: Johnson and Johnson - September 12, 2021 Category: Pharmaceuticals Source Type: news

New Analyses Suggest Favorable Results for STELARA ® (ustekinumab) When Used as a First-Line Therapy for Bio-Naïve Patients with Moderately to Severely Active Crohn’s Disease and Ulcerative Colitis
SPRING HOUSE, PENNSYLVANIA, October 25, 2021 – The Janssen Pharmaceutical Companies of Johnson & Johnson today announced data from two new analyses of STELARA® (ustekinumab) for the treatment of adults with moderately to severely active Crohn’s disease (CD) and ulcerative colitis (UC).1,2 In a modelled analysisa focused on treatment sequencing using data from randomized controlled trials, network meta-analysis and literature, results showed patient time spent in clinical remission or response was highest when STELARA was used as a first-line advanced therapy for bio-naïve patients with moderately to severely acti...
Source: Johnson and Johnson - October 25, 2021 Category: Pharmaceuticals Tags: Innovation Source Type: news