The applications of data mining and machine learning in Bangladesh for disease pattern analysis and prediction

The applications of data mining and machine learning in Bangladesh for disease pattern analysis and prediction

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.

Bibliografiske detaljer
Hovedforfatter:	Mahmud, Mahmudul Hasan
Andre forfattere:	Arif, Hossain
Format:	Thesis
Sprog:	en_US
Udgivet:	Brac University 2021
Fag:	Diabetes prediction Naïve Bayes Decision tree Random forest Logistic regression SVC Linear SVC KNN LassoCV GridsearchCV KFold StratifiedKFold
Online adgang:	http://dspace.bracu.ac.bd/xmlui/handle/10361/14450

Lignende værker

A feature selection approach to determine obesity using machine learning method
af: Antor, Shahidul Alam, et al.
Udgivet: (2021)

Flood prediction using machine learning models
af: Syeed, Miah Mohammad Asif, et al.
Udgivet: (2022)

Identification of fake news using machine learning in distributed system
af: Saif, Mehruz, et al.
Udgivet: (2021)

A supervised learning approach by machine learning and deep learning algorithms to predict type II DM risk
af: Farabe, Abdullah Al, et al.
Udgivet: (2021)

SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
af: Alam, Auninda, et al.
Udgivet: (2021)

Heart disease prediction using techniques of classification in machine learning
af: Afrose, Sadia, et al.
Udgivet: (2021)

Machine learning In breast cancer prognosis and prediction
af: Chowdhury, Shah Abul Hasnat, et al.
Udgivet: (2023)

A voice signal based gender prediction model using random forest classifier
af: Ahmed, Saif, et al.
Udgivet: (2018)

Stock market prediction using ensemble learning
af: Rabbani, Rakin Bin, et al.
Udgivet: (2021)

Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations
af: Rabbi, Md. Nafis
Udgivet: (2024)

Machine learning based analysis and prediction of crop yield and prices of Aman, Aus and Boro rice
af: Bhattacharjee, Ruposri, et al.
Udgivet: (2024)

Parking data analysis
af: Ahamed, Kasfi, et al.
Udgivet: (2023)

Prediction of diabetes induced complications using different machine learning algorithms
af: Rahman, Tahsinur, et al.
Udgivet: (2018)

Estimating flood susceptibility of Bangladesh in the future year using machine learning
af: Alim, Sakib Bin, et al.
Udgivet: (2021)

OpenCV 2 computer vision application programming cookbook : over 50 recipes to master this library of programming functions for real-time computer vision /
af: Laganière,R
Udgivet: (2011)

Sentimental analysis of food review contents to improve food culture and the quality of virtual content using natural language processing and machine learning
af: Sarkar, Ripa, et al.
Udgivet: (2024)

A color vision approach considering Reflection Co efficient based on Autoencoder techniques using deep neural networks
af: Mahmud, Shakib Izaz, et al.
Udgivet: (2022)

Early grade prediction using profile data
af: Iqbal, Sumaiya, et al.
Udgivet: (2021)

Best feature selection and data visualization for breast cancer prediction
af: Hemel, Tanjim Ahmed, et al.
Udgivet: (2020)

Cardiovascular disease prediction model using Machine Learning Algorithm
af: Arefin Mirdha, MD Shamsul
Udgivet: (2023)

Analysis on the effects of wallstreetbets on the stock market
af: Hossain, Abir, et al.
Udgivet: (2022)

A machine learning approach to predict young voter enthusiasm based on non-political factors
af: Rahman, Md. Nowroz Junaed, et al.
Udgivet: (2021)

Detecting online recruitment fraud by using machine learning
af: Ghosh, Gitanjali, et al.
Udgivet: (2021)

A counseling system to predict the study path for freshmen
af: Usha, Rowshni Tasneem, et al.
Udgivet: (2019)

Machine learning for stress prediction
af: Salehin, Sherajus, et al.
Udgivet: (2023)

Automated fabric color prediction
af: Muhtashima, Fawzia, et al.
Udgivet: (2024)

Prediction of bipolar disorder from mental episodes using machine learning approach
af: Tasmeem, Sumaiya, et al.
Udgivet: (2023)

Predicting subject area interest of a student using naive bayes
af: Hossain, Shakib
Udgivet: (2016)

Performance analysis of machine learning algorithms for Malware classification
af: Bushra, Raisa Hasan, et al.
Udgivet: (2023)

A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
af: Rahee, Arnob, et al.
Udgivet: (2021)

Football offside tracking
af: Mitu, Ishrat Jahan, et al.
Udgivet: (2023)

Fighting depression: psychological approaches among Bangladeshi university students
af: Sen, Sanjib Kumar, et al.
Udgivet: (2022)

A novel approach to reduce air pollution through machine learning based PM2.5 prediction
af: Alif, Omar Farhad, et al.
Udgivet: (2023)

Prediction on large scale data using extreme gradient boosting
af: Sawon, Md.Tariq Hasan, et al.
Udgivet: (2016)

Forecasting stock market prices using advanced tools of machine learning
af: Anwar, Md. Tawhid, et al.
Udgivet: (2019)

Predicting the length of stay in a hospital for a particular disease using machine learning algorithms
af: Imam, Saif
Udgivet: (2021)

Modelling and forecasting energy demand of Bangladesh using AI based algorithms
af: Mahmud, Booshra Nazifa, et al.
Udgivet: (2019)

Data analysis on the Bangladesh share market using Machine-Learning
af: Sadman, Syed Hassan, et al.
Udgivet: (2021)

Analyzing CV/resume using natural language processing and machine learning
af: Reza, Md. Tanzim, et al.
Udgivet: (2018)

An approach to detect epileptic seizure using XAI and machine learning
af: Bijoy, Emam Hasan, et al.
Udgivet: (2022)