Prediction of bipolar disorder from mental episodes using machine learning approach

Prediction of bipolar disorder from mental episodes using machine learning approach

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Bibliografiske detaljer
Main Authors:	Tasmeem, Sumaiya, Rahaman, Motiur, Piasha, Karishma Meherin Khan, Yasar, Samin, Dina, Murshida Akter
Andre forfattere:	Rahman, Tanvir
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2023
Fag:	Bipolar detection Random forest Machine learning Extreme gradient boosting Decision tree SVM MDQ Logistic regression CatBoost Light-GBM XGBoost Logistic regression analysis Deep learning (Machine learning)
Online adgang:	http://hdl.handle.net/10361/21779

Lignende værker

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

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

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

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

Building a credit scoring model to assign a reference score based on credit transaction and relevant profile data
af: Islam, Saqib Al, et al.
Udgivet: (2020)

Comparative analysis and implementation of credit risk prediction through distinct machine learning models
af: Turjo, Aquib Abtahi, et al.
Udgivet: (2021)

Unleashing potential: a data-driven exploration of identifying player potentialities through advanced analytics in sports
af: Bhowmik, Prashanta, et al.
Udgivet: (2024)

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

Prediction of earthquakes: a step towards predicting the unpredictable
af: Chowdhury, Maheen, et al.
Udgivet: (2023)

Flood prediction using ensemble machine learning models
af: Rahman, Tanvir
Udgivet: (2024)

Early detection of chronic kidney disease using machine learning
af: Abrar, Tahmid, et al.
Udgivet: (2019)

Predicting stock market trend from twitter feed and building a framework for Bangladesh
af: Karim, Shabab, et al.
Udgivet: (2018)

A thesis on utilizing machine learning models to predict material hardship
af: Das, Tirtha
Udgivet: (2024)

Prediction and detection in change of cognitive load for VIP’s by a machine learning approach
af: Rahman, Fahim, et al.
Udgivet: (2021)

Where will you setup your business next?: a machine learning approach to suggest ideal geographical location for new restaurant establishment
af: Shihab, Ibne Farabi, et al.
Udgivet: (2018)

Speech emotion detection using supervised, unsupervised and feature selection algorithms
af: Rifat, Abu Nuraiya Mahfuza Yesmin, et al.
Udgivet: (2019)

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

Performance analysis of machine learning algorithms in resume recommendation systems
af: Hasan, Ibteaz, et al.
Udgivet: (2018)

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

Polycystic ovary syndrome detection using neural network.
af: Istiyaq, Tahsin, et al.
Udgivet: (2024)

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

Performance analysis of different machine learning approaches for single modal facial expression detection
af: Zinia, Surovi, et al.
Udgivet: (2018)

ML based career suggestive system for informal job sector considering cognitive skills
af: Tonny, Ms. Ayesha Siddika, et al.
Udgivet: (2023)

Early detection of breast cancer using machine learning
af: Fuad, Wasi Mohammad
Udgivet: (2019)

A machine learning approach to detect depression and anxiety using supervised learning
af: Ullas, Md Tahmidur Rahman, et al.
Udgivet: (2019)

Analyzing the security of e-Health data based on a hybrid federated learning model
af: Shafin, Md. Mehtabul Islam, et al.
Udgivet: (2023)

Application of CNN based architectures in detection of distracted drivers
af: Arafin, Irfana, et al.
Udgivet: (2023)

Weather forecasting using Deep Learning
af: Fahad, Sheikh Abdul, et al.
Udgivet: (2023)

Exploring machine learning techniques for symptom-based detection of livestock diseases
af: Niloy, Mahir Ahmed, et al.
Udgivet: (2024)

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

Application of machine learning techniques on the context of predicting upcoming traffic congestion and providing the best preferred path
af: Saquib, Muhammad Sadman, et al.
Udgivet: (2019)

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)

Sentiment analysis for Bengali newspaper headlines
af: Hossain, Mohammad Samman, et al.
Udgivet: (2017)

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

Analysis on dengue severity using machine learning approach
af: Sayeed, Sanjana, et al.
Udgivet: (2021)

Machine learning for stress prediction
af: Salehin, Sherajus, 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)

Application of machine learning techniques on the context of livestock analysis
af: Islam, Md. Shajedul, et al.
Udgivet: (2018)

Nonparametric bootstrapping for multiple logistic regression model using R
af: Hossain, Ahmed, et al.
Udgivet: (2010)

Statistical analysis of network data flows and predictions using statistical and machine learning regression models
af: Boateng, Albert, et al.
Udgivet: (2024)