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Field: Machine Learning in Healthcare

Can AI Help in Screening Viral and COVID-19 Pneumonia?

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Muhammad E. H. Chowdhury, Tawsifur Rahman, Amith Khandakar, Rashid Mazhar et al.

Journal: IEEE Access
Year: 2020
Citations: 1898

Coronavirus disease (COVID-19) is a pandemic disease, which has already caused thousands of causalities and infected several millions of people worldwide. Any technological tool enabling rapid screening of the COVID-19 infection with high accuracy can be crucially helpful to the healthcare professio...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Efficient Prediction of Cardiovascular Disease Using Machine Learning Algorithms With Relief and LASSO Feature Selection Techniques

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Pronab Ghosh, Sami Azam, Mirjam Jonkman, Asif Karim et al.

Journal: IEEE AccessYear: 2021Citations: 571

Cardiovascular diseases (CVD) are among the most common serious illnesses affecting human health. CVDs may be prevented or mitigated by early diagnosis, and this may reduce mortality rates. Identifying risk factors using machine learning models is a promising approach. We would like to propose a mod...

Health SciencesHealth ProfessionsHealth Information ManagementOpen Access
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Heart disease prediction using supervised machine learning algorithms: Performance analysis and comparison

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Md. Mamun Ali, Bikash Kumar Paul, Kawsar Ahmed, Francis M. Bui et al.

Journal: Computers in Biology and MedicineYear: 2021Citations: 480

Machine learning and data mining-based approaches to prediction and detection of heart disease would be of great clinical utility, but are highly challenging to develop. In most countries there is a lack of cardiovascular expertise and a significant rate of incorrectly diagnosed cases which could be...

Health SciencesHealth ProfessionsHealth Information Management
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Shifting machine learning for healthcare from development to deployment and from models to data

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Angela Zhang, Lei Xing, James Zou, Joseph C. Wu

Journal: Nature Biomedical EngineeringYear: 2022Citations: 392

In the past decade, the application of machine learning (ML) to healthcare has helped drive the automation of physician tasks as well as enhancements in clinical capabilities and access to care. This progress has emphasized that, from model development to model deployment, data play central roles. I...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Natural Language Processing in Electronic Health Records in relation to healthcare decision-making: A systematic review

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Elias Hossain, Rajib Rana, Niall Higgins, Jeffrey Soar et al.

Journal: Computers in Biology and MedicineYear: 2023Citations: 361

BACKGROUND Natural Language Processing (NLP) is widely used to extract clinical insights from Electronic Health Records (EHRs). However, the lack of annotated data, automated tools, and other challenges hinder the full utilisation of NLP for EHRs. Various Machine Learning (ML), Deep Learning (DL) an...

Physical SciencesComputer ScienceArtificial Intelligence
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Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson’s disease and schizophrenia

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Manan Binth Taj Noor, Nusrat Zerin Zenia, M. Shamim Kaiser, Shamim Al Mamun et al.

Journal: Brain InformaticsYear: 2020Citations: 335

Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have o...

Life SciencesNeuroscienceNeurologyOpen Access
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Comparative approaches for classification of diabetes mellitus data: Machine learning paradigm

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Md. Maniruzzaman, Nishith Kumar, Md. Menhazul Abedin, Md. Shaykhul Islam et al.

Journal: Computer Methods and Programs in BiomedicineYear: 2017Citations: 269

Background and objective Diabetes is a silent killer. The main cause of this disease is the presence of excessive amounts of metabolites such as glucose. There were about 387 million diabetic people all over the world in 2014. The financial burden of this disease has been calculated to be about $13,...

Health SciencesHealth ProfessionsHealth Information Management
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Coronary Artery Heart Disease Prediction: A Comparative Study of Computational Intelligence Techniques

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Safial Islam Ayon, Md. Milon Islam, Md Rahat Hossain

Journal: IETE Journal of ResearchYear: 2020Citations: 256

Diseases is an unusual circumstance that affects single or more parts of a human’s body. Because of lifestyle and patrimonial, different kinds of disease are increasing day by day. Among all those diseases, heart disease turns out to be the most common disease and the impact of this ailment is dange...

Health SciencesHealth ProfessionsHealth Information ManagementOpen Access
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Diabetes Prediction: A Deep Learning Approach

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Safial Islam Ayon, Md. Milon Islam

Journal: International Journal of Information Engineering and Electronic BusinessYear: 2019Citations: 210

Nowadays, Diabetes is one of the most common and severe diseases in Bangladesh as well as all over the world. It is not only harmful to the blood but also causes different kinds of diseases like blindness, renal disease, kidney problem, heart diseases etc. that causes a lot of death per year. So, it...

Health SciencesHealth ProfessionsHealth Information ManagementOpen Access
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AlzheimerNet: An Effective Deep Learning Based Proposition for Alzheimer’s Disease Stages Classification From Functional Brain Changes in Magnetic Resonance Images

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F. M. Javed Mehedi Shamrat, Shamima Akter, Sami Azam, Asif Karim et al.

Journal: IEEE AccessYear: 2023Citations: 184

Alzheimer’s disease is largely the underlying cause of dementia due to its progressive neurodegenerative nature among the elderly. The disease can be divided into five stages: Subjective Memory Concern (SMC), Mild Cognitive Impairment (MCI), Early MCI (EMCI), Late MCI (LMCI), and Alzheimer’s Disease...

Life SciencesNeuroscienceNeurologyOpen Access
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A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When?

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Subrato Bharati, M. Rubaiyat Hossain Mondal, Prajoy Podder

Journal: IEEE Transactions on Artificial IntelligenceYear: 2023Citations: 173

Artificial intelligence (AI) models are increasingly finding applications in the field of medicine. Concerns have been raised about the explainability of the decisions that are made by these AI models. In this article, we give a systematic analysis of explainable artificial intelligence (XAI), with ...

Health SciencesMedicineHealth InformaticsOpen Access
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Machine learning based diabetes prediction and development of smart web application

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Nazin Ahmed, Rayhan Ahammed, Md. Manowarul Islam, Md. Ashraf Uddin et al.

Journal: International Journal of Cognitive Computing in EngineeringYear: 2021Citations: 170

Diabetes is a very common disease affecting individuals worldwide. Diabetes increases the risk of long-term complications including heart disease, and kidney failure among others. People might live longer and lead healthier lives if this disease is detected early. Different supervised machine learni...

Health SciencesHealth ProfessionsHealth Information ManagementOpen Access
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Performance Analysis of Machine Learning Techniques to Predict Diabetes Mellitus

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Md Faruque, Asaduzzaman Asaduzzaman, Iqbal H. Sarker

Year: 2019Citations: 159

Diabetes mellitus is a common disease of human body caused by a group of metabolic disorders where the sugar levels over a prolonged period is very high. It affects different organs of the human body which thus harm a large number of the body's system, in particular the blood veins and nerves. Early...

Health SciencesHealth ProfessionsHealth Information Management
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Early Prediction of Diabetes Using an Ensemble of Machine Learning Models

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Aishwariya Dutta, Md. Kamrul Hasan, Mohiuddin Ahmad, Md. Abdul Awal et al.

Journal: International Journal of Environmental Research and Public HealthYear: 2022Citations: 153

Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of significant complications, including cardiovascular disease, kidney failure, diabetic retinopathy, and neuropathy, among others, which contribute to an increase in morbidity and mortality rate. If diabetes ...

Health SciencesHealth ProfessionsHealth Information ManagementOpen Access
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An Ensemble Approach for the Prediction of Diabetes Mellitus Using a Soft Voting Classifier with an Explainable AI

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Hafsa Binte Kibria, Md. Nahiduzzaman, Md. Omaer Faruq Goni, Mominul Ahsan et al.

Journal: SensorsYear: 2022Citations: 124

Diabetes is a chronic disease that continues to be a primary and worldwide health concern since the health of the entire population has been affected by it. Over the years, many academics have attempted to develop a reliable diabetes prediction model using machine learning (ML) algorithms. However, ...

Health SciencesHealth ProfessionsHealth Information ManagementOpen Access
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