Latest trends on heart disease prediction using machine learning and image fusion

Diwakar, Manoj; Tripathi, Amrendra; Joshi, Kapil; Memoria, Minakshi; Singh, Prabhishek; Kumar, Neeraj

doi:10.1016/j.matpr.2020.09.078

Cited by 98 publications

(29 citation statements)

References 10 publications

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“…The Covid-19 increased the problems to heart patient [19] that related with the many other factors. On the other hand, all the infected people may cured by sufficient facilities.…”

Section: Discussionmentioning

confidence: 99%

WITHDRAWN: Medical oxygen supply during COVID-19: A study with specific reference to State of Andhra Pradesh, India

Bikkina

Manda

Rao

2021

Materials Today: Proceedings

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“…The Covid-19 increased the problems to heart patient [19] that related with the many other factors. On the other hand, all the infected people may cured by sufficient facilities.…”

Section: Discussionmentioning

confidence: 99%

WITHDRAWN: Medical oxygen supply during COVID-19: A study with specific reference to State of Andhra Pradesh, India

Bikkina

Manda

Rao

2021

Materials Today: Proceedings

View full text Add to dashboard Cite

“…The Covid-19 expanded the issues to heart patient [18] that related with the numerous different components. Then again, every one of the contaminated individuals may relieved by adequate offices.…”

Section: Discussionmentioning

confidence: 99%

Estimation of Oxygen Cylinder Availability and Classification of Its Types, Suitability Using Machine Learning and Data Analysis

Sinha¹

2021

Preprint

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This is break direction on oxygen sources and conveyance methodologies for COVID-19 treatment. It has been adjusted from WHO and UNICEF's specialized details and direction for oxygen treatment gadgets, which is important for the WHO clinical gadget specialized arrangement, 1 and depends on current information on the circumstance in China and different nations where cases have been distinguished. This direction is proposed for wellbeing office chairmen, clinical leaders, acquisition officials, arranging officials, biomedical architects, foundation engineers and strategy producers. It portrays how to: measure oxygen interest, to distinguish oxygen sources that are accessible, and select suitable flood sources to best react to COVID-19 patients' requirements, particularly in low-and-center pay nations. WHO will refresh these suggestions as new data opens up. Coronavirus pandemic spurred fake interest for oxygen gas chambers for clinical use - both at emergency clinics and inquisitively, for home use by patients. A few patients and surprisingly sound people investigate the conceivable outcomes and likely benefits of utilizing oxygen from chambers for private utilization. Be that as it may, this isn't continuously protected, and sufficient safety measures are to be taken, bombing which there can be fatalities. This paper investigates the significance of keeping up satisfactory degrees of oxygen levels appropriate for human utilization. It advises the clinical use and the advantages and disadvantages of putting away oxygen chambers at home. The investigation likewise addresses lawful and administrative perspectives. The investigation's discoveries can help people settle on an educated choice on the protected use regarding oxygen gas. Further, it cautions on the expanded significance of guidelines and limiting access and use. This paper aims at designing an oxygen level monitoring technique in an oxygen cylinder. The amount of oxygen present inside the oxygen cylinder is very vital information when such cylinder is in use for supply of oxygen to a critical patient. The amount of oxygen present inside the cylinder is measured by the pressure at the outlet nozzle. The pressure is measured using a high precision MEMS Pressure Sensor. The output of the MEMS pressure sensor is voltage of the order milli. An amplifier is used to amplify this milli volt signal. A microcontroller is used in cascade to process the signal and display the pressure of oxygen cylinder.

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“…In literature, most of the studies proposed fusion frameworks perform multi-modal fusion of different medical signals (e.g., ECG, EEG, etc.) [7] or imaging modalities (e.g., MRI, PET, CT, or CXR) [32], [33]. To resolve the issues of multi-source data fusion a genetic algorithm was proposed to select data from source having optimal information [34].…”

Section: A Multi-modal Data Fusionmentioning

confidence: 99%

Performance Enhancement of Predictive Analytics for Health Informatics Using Dimensionality Reduction Techniques and Fusion Frameworks

2022

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Predictive analytics has become an essential area of research in health informatics. The availability of multi-source and multi-modal data in healthcare has made the disease prediction, diagnosis, and medication process more effective and reliable. However, the analysis and decision making have become challenging task, particularly when data is in multiple formats and from different sources. In this study, different frameworks have been proposed to handle multi-nature data at different levels for predictive analytics. Dimensionality reduction techniques have been applied to extract relevant features to enhance the analysis. To improve the performance of predictive analytics at different fusion levels, the potential benefits of multi-modal data have been discussed. Moreover, notable improvement in prediction accuracy has been observed through experimental evaluation of the proposed frameworks. Furthermore, the issues which have been found during dimension reduction and fusion approaches have also been highlighted.

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Latest trends on heart disease prediction using machine learning and image fusion

Cited by 98 publications

References 10 publications

WITHDRAWN: Medical oxygen supply during COVID-19: A study with specific reference to State of Andhra Pradesh, India

WITHDRAWN: Medical oxygen supply during COVID-19: A study with specific reference to State of Andhra Pradesh, India

Estimation of Oxygen Cylinder Availability and Classification of Its Types, Suitability Using Machine Learning and Data Analysis

Performance Enhancement of Predictive Analytics for Health Informatics Using Dimensionality Reduction Techniques and Fusion Frameworks

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