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Deep deterministic learning for pattern recognition of different cardiac diseases through the internet of medical things

- Iqbal, Uzair, Wah, Teh, Habib ur Rehman, Muhammad, Mujtaba, Ghulam, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Iqbal, Uzair , Wah, Teh , Habib ur Rehman, Muhammad , Mujtaba, Ghulam , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Journal of Medical Systems Vol. 42, no. 12 (2018), p.
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  • Description: Electrocardiography (ECG) sensors play a vital role in the Internet of Medical Things, and these sensors help in monitoring the electrical activity of the heart. ECG signal analysis can improve human life in many ways, from diagnosing diseases among cardiac patients to managing the lifestyles of diabetic patients. Abnormalities in heart activities lead to different cardiac diseases and arrhythmia. However, some cardiac diseases, such as myocardial infarction (MI) and atrial fibrillation (Af), require special attention due to their direct impact on human life. The classification of flattened T wave cases of MI in ECG signals and how much of these cases are similar to ST-T changes in MI remain an open issue for researchers. This article presents a novel contribution to classify MI and Af. To this end, we propose a new approach called deep deterministic learning (DDL), which works by combining predefined heart activities with fused datasets. In this research, we used two datasets. The first dataset, Massachusetts Institute of Technology–Beth Israel Hospital, is publicly available, and we exclusively obtained the second dataset from the University of Malaya Medical Center, Kuala Lumpur Malaysia. We first initiated predefined activities on each individual dataset to recognize patterns between the ST-T change and flattened T wave cases and then used the data fusion approach to merge both datasets in a manner that delivers the most accurate pattern recognition results. The proposed DDL approach is a systematic stage-wise methodology that relies on accurate detection of R peaks in ECG signals, time domain features of ECG signals, and fine tune-up of artificial neural networks. The empirical evaluation shows high accuracy (i.e., ≤99.97%) in pattern matching ST-T changes and flattened T waves using the proposed DDL approach. The proposed pattern recognition approach is a significant contribution to the diagnosis of special cases of MI. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

The differences in the prevalence of cardiovascular disease, its risk factors, and achievement of therapeutic goals among urban and rural primary care patients in Poland: Results from the LIPIDOGRAM 2015 study

- Studziński, Krzysztof, Tomasik, Tomasz, Windak, Adam, Banach, Maciej, Charchar, Fadi

  • Authors: Studziński, Krzysztof , Tomasik, Tomasz , Windak, Adam , Banach, Maciej , Charchar, Fadi
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Journal of Clinical Medicine Vol. 10, no. 23 (2021), p.
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  • Description: A nationwide cross-sectional study, LIPIDOGRAM2015, was carried out in Poland in the years 2015 and 2016. A total of 438 primary care physicians enrolled 13,724 adult patients that sought medical care in primary health care practices. The prevalence of hypertension, diabetes mellitus, dyslipidaemia, and CVD were similar in urban and rural areas (49.5 vs. 49.4%; 13.7 vs. 13.1%; 84.2 vs. 85.2%; 14.4 vs. 14.2%, respectively). The prevalence of obesity (32.3 vs. 37.5%, p < 0.01) and excessive waist circumference (77.5 vs. 80.7%, p < 0.01), as well as abdominal obesity (p = 43.2 vs. 46.4%, p < 0.01), were higher in rural areas in both genders. Mean levels of LDL-C (128 vs. 130 mg/dL, p = 0.04) and non-HDL-C (147 vs. 148 mg/dL, p = 0.03) were slightly higher in rural populations. Altogether, 14.3% of patients with CVD from urban areas and 11.3% from rural areas reached LDL <70 mg/dL (p = 0.04). There were no important differences in the prevalence of hypertension, diabetes, dyslipidaemia, and CVD, or in mean levels of blood pressure, cholesterol fractions, glucose, and HbA1c between Polish urban and rural primary care patient populations. A high proportion of patients in cities and an even-higher proportion in rural areas did not reach the recommended targets for blood pressure, LDL-C, and HbA1c, indicating the need for novel CVD-prevention programs. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Fadi Charchar” is provided in this record**

Coping with chronic cardiovascular disease in Iran : a qualitative study

- Kalantarzadeh, Mozhgan, Alavi, Mousa, Yousefi, Hojatollah, Maghsoudi, Jahangir, Hungerford, Catherine, Cleary, Michelle

  • Authors: Kalantarzadeh, Mozhgan , Alavi, Mousa , Yousefi, Hojatollah , Maghsoudi, Jahangir , Hungerford, Catherine , Cleary, Michelle
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Nursing and Health Sciences Vol. 23, no. 4 (2021), p. 843-851
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  • Description: The effects of chronic cardiovascular disease can challenge the achievement of treatment goals and recovery outcomes. This study explores the ways in which patients cope with the effects of chronic cardiovascular disease, from the perspectives of patients, family caregivers, and health professionals. The qualitative study was conducted from May 2019 to September 2020 in Isfahan, Iran. Thirteen people with chronic cardiovascular disease, 6 family caregivers, and 16 healthcare professionals participated in semi-structured individual interviews. Transcripts were analysed thematically. Findings suggest that people with chronic cardiovascular disease use a range of coping strategies, both positive and negative, to adjust to their conditions. The positive strategies include managing their health-related symptoms, drawing on religious or spiritual beliefs, and accessing social and relational supports. Negative strategies can include over-reliance on family members for support, leading to reduced activity and loss of independence. Understanding the nature of the strategies used by patients provides an important means by which health service providers can support patients to further develop positive coping strategies. This, in turn, will enable patients to achieve higher levels of wellbeing. © 2021 John Wiley & Sons Australia, Ltd.
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