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Total 162 results found since Jan 2013.
IJERPH, Vol. 18, Pages 11302: Review of Deep Learning-Based Atrial Fibrillation Detection Studies
Rajendra Acharya
Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming and prone to errors. To overcome these limitations, computer-aided diagnosis systems are developed using artificial intelligence techniques for automated detection of AF. Various machine learning and deep learning (DL) techniques have been developed for the automated detection of AF. In this review, we focused on the automated AF detection models developed using DL techniques. Twenty-four relevant articles published in intern...
Source: International Journal of Environmental Research and Public Health - October 28, 2021 Category: Environmental Health Authors: Fatma Murat Ferhat Sadak Ozal Yildirim Muhammed Talo Ender Murat Murat Karabatak Yakup Demir Ru-San Tan Udyavara Rajendra Acharya Tags: Review Source Type: research
Erectile Dysfunction Associated With Use of E-Cigarettes, Report Finds
This study highlights a novel finding that ENDS use could have serious implications on men’s se xual health.”El-Shahawy and colleagues analyzed data collected from December 2016 to January 2018 as part of thePopulation Assessment of Tobacco or Health (PATH) study —a national longitudinal study of tobacco use and how it affects the health of people in the United States. The researchers specifically focused on male participants 20 years and older who responded to questions about erectile dysfunction; their use of ENDS; current or past history of smoking; and previous diagnoses of diabetes, hypertension, high cholestero...
Source: Psychiatr News - December 7, 2021 Category: Psychiatry Tags: American Journal of Preventive Medicine E-cigarettes erectile dysfunction PATH Study Source Type: research
Contemporary management of persistent atrial fibrillation
Learning objectives Develop a basic understanding of the underlying mechanisms of atrial fibrillation and classification of the disease. Review the main principles in contemporary management of atrial fibrillation with a focus on persistent atrial fibrillation. Discuss catheter ablation in the context of atrial fibrillation. Introduction Atrial fibrillation (AF) is a multisystemic disorder that is associated with an excess risk of stroke, heart failure and mortality.1 It remains the most common sustained arrhythmia and its significance should not be underestimated. Research focused on unveiling the mechanisms of AF began o...
Source: Heart - December 22, 2021 Category: Cardiology Authors: Gupta, D., Ding, W. Y. Tags: Education in Heart Source Type: research
Handling of derived imbalanced dataset using XGBoost for identification of pulmonary embolism —a non-cardiac cause of cardiac arrest
AbstractRelationship between pulmonary embolism and heart failure is presented in this paper. The proposed research is divided into two phases. The first phase includes the establishment of a novel database with the help of a Cleveland ’s database for cardiology in order to establish a link between pulmonary embolism and heart failure. The connectivity is based on the relationship between the stroke volume and the pulse pressure (Pp < 25% (ap_hi)). The second phase includes the applicability of machine learning on the novel database. Novel database formed in this work is imbalanced, resulting in the overfitting p...
Source: Medical and Biological Engineering and Computing - January 13, 2022 Category: Biomedical Engineering Source Type: research
Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine
CONCLUSIONSIn patients with T2DM and ASCVD, cluster analysis identified four clinically distinct groups. Further cardiovascular phenotyping is warranted to inform patient care and optimize clinical trial designs.
Source: Diabetes Care - October 29, 2021 Category: Endocrinology Source Type: research
Janssen Data at ASCO GU Demonstrate Longstanding Leadership in Prostate Cancer and Commitment to Advancing Potential New Therapeutic Options for Genitourinary Cancers
Raritan, NJ, Feb. 1, 2022 – The Janssen Pharmaceutical Companies of Johnson & Johnson announced today that 17 presentations will be featured at the 2022 American Society of Clinical Oncology Genitourinary (ASCO GU) Cancers Symposium, taking place in San Francisco and virtually from February 17-19. Building on its long-term leadership in prostate cancer, Janssen is committed to advancing innovative treatments and transforming patient experiences, while focusing on research that may drive better outcomes for people across the genitourinary cancer spectrum. Data to be presented include Phase 3 results for the selective ...
Source: Johnson and Johnson - February 1, 2022 Category: Pharmaceuticals Tags: Innovation Source Type: news
Predicting Hospital Readmissions from Health Insurance Claims Data: A Modeling Study Targeting Potentially Inappropriate Prescribing
CONCLUSION: PIP successfully predicted readmissions for most diseases, opening the possibility for interventions to improve these modifiable risk factors. Machine-learning methods appear promising for future modeling of PIP predictors in complex older patients with many underlying diseases.PMID:35144291 | DOI:10.1055/s-0042-1742671
Source: Methods of Information in Medicine - February 10, 2022 Category: Information Technology Authors: Alexander Gerharz Carmen Ruff Lucas Wirbka Felicitas Stoll Walter E Haefeli Andreas Groll Andreas D Meid Source Type: research
New ERLEADA ® (apalutamide) Analysis Demonstrates Rapid, Deep Prostate-Specific Antigen (PSA) Response in Patients with Metastatic Castration-Sensitive Prostate Cancer (mCSPC)
SAN FRANCISCO, Feb. 14, 2022 – The Janssen Pharmaceutical Companies of Johnson & Johnson today announced new real-world evidence data showing the initiation of ERLEADA® (apalutamide) results in high rates of rapid and deep prostate-specific antigen (PSA) response among patients with metastatic castration-sensitive prostate cancer (mCSPC). In a separate post-hoc analysis of the registrational Phase 3 SPARTAN and TITAN studies, rapid and deep PSA responses with ERLEADA® were associated with improvement in patient-reported outcomes (PROs) related to quality of life, physical wellbeing, pain, and fatigue intensity. The...
Source: Johnson and Johnson - February 14, 2022 Category: Pharmaceuticals Tags: Innovation Source Type: news
Sensors, Vol. 22, Pages 1776: Compressed Deep Learning to Classify Arrhythmia in an Embedded Wearable Device
In conclusion, Mobilenet would be a more efficient model than Resnet to classify arrhythmia in an embedded wearable device.
Source: Sensors - February 24, 2022 Category: Biotechnology Authors: Kwang-Sig Lee Hyun-Joon Park Ji Eon Kim Hee Jung Kim Sangil Chon Sangkyu Kim Jaesung Jang Jin-Kook Kim Seongbin Jang Yeongjoon Gil Ho Sung Son Tags: Article Source Type: research
IJERPH, Vol. 19, Pages 4014: Automated Detection of Hypertension Using Continuous Wavelet Transform and a Deep Neural Network with Ballistocardiography Signals
Acharya
Managing hypertension (HPT) remains a significant challenge for humanity. Despite advancements in blood pressure (BP)-measuring systems and the accessibility of effective and safe anti-hypertensive medicines, HPT is a major public health concern. Headaches, dizziness and fainting are common symptoms of HPT. In HPT patients, normalcy may be observed at one instant and abnormality may prevail during a long duration of 24 h ambulatory BP. This may cause difficulty in identifying patients with HPT, and hence there is a possibility that individuals may be untreated or administered insufficiently. Most importantly, u...
Source: International Journal of Environmental Research and Public Health - March 28, 2022 Category: Environmental Health Authors: Jaypal Singh Rajput Manish Sharma T. Sudheer Kumar and U. Rajendra Acharya Tags: Article Source Type: research
A proteomic model shows potential as a surrogate end point for CVD risk
Nature Reviews Cardiology, Published online: 20 April 2022; doi:10.1038/s41569-022-00716-7A model generated using proteomics and machine learning that included 27 proteins was able to predict the 4-year risk of myocardial infarction, heart failure, stroke or all-cause death better than a clinical model and was sensitive to the adverse and beneficial changes in outcome.
Source: Nature Reviews Cardiology - April 20, 2022 Category: Cardiology Authors: Irene Fern ández-Ruiz Source Type: research
Po-661-03 use of a deep learning algorithm to predict paroxysmal atrial fibrillation based on printed electrocardiographic records acquired during sinus rhythm
Atrial fibrillation (AF) is a common type of sustained arrhythmia worldwide. Asymptomatic AF, which occurs frequently, is associated with an increased incidence of ischemic stroke, heart failure, and mortality. A large number of patients with paroxysmal atrial fibrillation (PAF) remain undiagnosed due to the absence of electrocardiographic evidence of AF (AF-ECGs). If PAF could be predicted, targeted screening could improve early detection and treatment of this condition.
Source: Heart Rhythm - April 29, 2022 Category: Cardiology Authors: Yang Zhou, Yu Chen, Deyun Zhang, Shijia Geng, Guodong Wei, Ying Tian, Shenda Hong, XINGPENG LIU Source Type: research
Sensors, Vol. 22, Pages 4310: Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning
In this study, we aimed at diagnosing CVD using a novel approach integrating information from retinal images and DXA data. We considered an adult Qatari cohort of 500 participants from Qatar Biobank (QBB) with an equal number of participants from the CVD and the control groups. We designed a case-control study with a novel multi-modal (combining data from multiple modalities&mdash;DXA and retinal images)&mdash;to propose a deep learning (DL)-based technique to distinguish the CVD group from the control group. Uni-modal models based on retinal images and DXA data achieved 75.6% and 77.4% accuracy, respective...
Source: Sensors - June 7, 2022 Category: Biotechnology Authors: Hamada R. H. Al-Absi Mohammad Tariqul Islam Mahmoud Ahmed Refaee Muhammad E. H. Chowdhury Tanvir Alam Tags: Article Source Type: research
Clinical code usage in UK general practice: a cohort study exploring 18 conditions over 14 years
Conclusions
This is an under-reported research area and the findings suggest the codes’ usage diversity for most conditions remained overall stable throughout the study period. Generated mental health code lists can last for a long time unlike cardiometabolic conditions and cancer. Adopting more consistent and less diverse coding would help improve data quality in primary care. Future research is needed following the transfer to the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) coding.
Source: BMJ Open - July 25, 2022 Category: General Medicine Authors: Zghebi, S. S., Reeves, D., Grigoroglou, C., McMillan, B., Ashcroft, D. M., Parisi, R., Kontopantelis, E. Tags: Open access, General practice / Family practice Source Type: research
