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Field: Health Information Management

A Belief Rule Based Expert System to Assess Tuberculosis under Uncertainty

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Mohammad Shahadat Hossain, Faisal Ahmed, Fatema-Tuj-Johora, Karl Andersson

Journal: Journal of Medical Systems
Year: 2017
Citations: 129

The primary diagnosis of Tuberculosis (TB) is usually carried out by looking at the various signs and symptoms of a patient. However, these signs and symptoms cannot be measured with 100 % certainty since they are associated with various types of uncertainties such as vagueness, imprecision, randomn...

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Liver Disease Prediction by Using Different Decision Tree Techniques

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Nazmun Nahar, Ferdous Ara

Journal: International Journal of Data Mining & Knowledge Management ProcessYear: 2018Citations: 128

Early prediction of liver disease is very important to save human life and take proper steps to control the disease. Decision Tree algorithms have been successfully applied in various fields especially in medical science. This research work explores the early prediction of liver disease using variou...

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A deep learning approach based on convolutional LSTM for detecting diabetes

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Md. Motiur Rahman, Dilshad Islam, Rokeya Jahan Mukti, Indrajit Saha

Journal: Computational Biology and ChemistryYear: 2020Citations: 127

Diabetes is a chronic disease that occurs when the pancreas does not generate sufficient insulin or the body cannot effectively utilize the produced insulin. If it remains unidentified and untreated, then it could be very deadliest. One can lead a healthy life with proper treatment if the presence o...

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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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Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model

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Mohammad Mafijul Islam, Morshed Alam, Md Tariquzaman, Mohammad Alamgir Kabir et al.

Journal: BMC Public HealthYear: 2013Citations: 120

BACKGROUND: Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomou...

Health SciencesHealth ProfessionsHealth Information ManagementOpen Access
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Analysis of data mining techniques for heart disease prediction

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Marjia Sultana, Afrin Haider, Mohammad Shorif Uddin

Year: 2016Citations: 116

Heart disease is considered as one of the major causes of death throughout the world. It cannot be easily predicted by the medical practitioners as it is a difficult task which demands expertise and higher knowledge for prediction. This paper addresses the issue of prediction of heart disease accord...

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Prediction of chronic liver disease patients using integrated projection based statistical feature extraction with machine learning algorithms

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Ruhul Amin, Rubia Yasmin, Sabba Ruhi, Md. Habibur Rahman et al.

Journal: Informatics in Medicine UnlockedYear: 2022Citations: 108

The healthy liver plays more than 500 organic roles in the human body, while a malfunction may be dangerous or even deadly. Early diagnosis and treatment of liver disease can improve the likelihood of survival. Machine learning (ML) is a powerful tool that can assist healthcare professionals during ...

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Reduction of Overfitting in Diabetes Prediction Using Deep Learning Neural Network

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Akm Ashiquzzaman, Abdul Kawsar Tushar, Md. Rashedul Islam, Dongkoo Shon et al.

Journal: Lecture notes in electrical engineeringYear: 2017Citations: 108

Accurate prediction of diabetes is an important issue in health prognostics. However, data overfitting degrades the prediction accuracy in diabetes prognosis. In this paper, a reliable prediction system for the disease of diabetes is presented using a dropout method to address the overfitting issue....

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Detection of the chronic kidney disease using XGBoost classifier and explaining the influence of the attributes on the model using SHAP

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Md. Johir Raihan, Md. Al-Masrur Khan, Seong‐Hoon Kee, Abdullah-Al Nahid

Journal: Scientific ReportsYear: 2023Citations: 107

Chronic kidney disease (CKD) is a condition distinguished by structural and functional changes to the kidney over time. Studies show that 10% of adults worldwide are affected by some kind of CKD, resulting in 1.2 million deaths. Recently, CKD has emerged as a leading cause of mortality worldwide, ma...

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Comprehensive Performance Assessment of Deep Learning Models in Early Prediction and Risk Identification of Chronic Kidney Disease

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Shamima Akter, Ahsan Habib, Md. Ashiqul Islam, Md. Sagar Hossen et al.

Journal: IEEE AccessYear: 2021Citations: 107

The incidence of chronic kidney disease (CKD) is rising rapidly around the globe. Asymptomatic CKD is common and guideline-directed monitoring to predict CKD by various factors is underutilized. Computer-aided automated diagnostic (CAD) can play a major role to predict CKD. CAD systems such as deep ...

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A Comprehensive Analysis on Detecting Chronic Kidney Disease by Employing Machine Learning Algorithms

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Mirza Muntasir Nishat, Fahim Faisal, Rezuanur Rahman Dip, Sarker Md. Nasrullah et al.

Journal: EAI Endorsed Transactions on Pervasive Health and TechnologyYear: 2021Citations: 106

INTRODUCTION: Chronic Kidney Disease refers to the slow, progressive deterioration of kidney functions. However, the impairment is irreversible and imperceptible up until the disease reaches one of the later stages, demanding early detection and initiation of treatment in order to ensure a good prog...

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Performance Evaluation of Random Forests and Artificial Neural Networks for the Classification of Liver Disorder

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Md. Rezwanul Haque, Md. Milon Islam, Hasib Iqbal, Md. Sumon Reza et al.

Journal: 2018 International Conference on Computer, Communication, Chemical, Material and Electronic Engineering (IC4ME2)Year: 2018Citations: 104

Liver is the major organ inside the human body which is very supportive for digesting food, eliminating poisons, and stocking energy. The rate of Liver disorder patients is rapidly rising all over the world. But it is very hard to identify the disorder from its ambiguous symptoms which increases the...

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Explainable AI-based Alzheimer’s prediction and management using multimodal data

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Sobhana Jahan, Kazi Abu Taher, M. Shamim Kaiser, Mufti Mahmud et al.

Journal: PLoS ONEYear: 2023Citations: 100

BACKGROUND: According to the World Health Organization (WHO), dementia is the seventh leading reason of death among all illnesses and one of the leading causes of disability among the world's elderly people. Day by day the number of Alzheimer's patients is rising. Considering the increasing rate and...

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Implementation of a Web Application to Predict Diabetes Disease: An Approach Using Machine Learning Algorithm

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Samrat Kumar Dey, Ashraf Hossain, Md. Mahbubur Rahman

Year: 2018Citations: 98

Diabetes is caused due to the excessive amount of sugar condensed into the blood. Currently, it is considered as one of the lethal diseases in the world. People all around the globe are affected by this severe disease knowingly or unknowingly. Other diseases like heart attack, paralyzed, kidney dise...

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Comparison of Various Classification Techniques Using Different Data Mining Tools for Diabetes Diagnosis

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Rashedur M. Rahman, Farhana Afroz

Journal: Journal of Software Engineering and ApplicationsYear: 2013Citations: 97

In the absence of medical diagnosis evidences, it is difficult for the experts to opine about the grade of disease with affirmation. Generally many tests are done that involve clustering or classification of large scale data. However many tests could complicate the main diagnosis process and lead to...

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