Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study

Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Biotechnology and Bachelor of Science in Microbiology, 2023.

Bibliografiske detaljer
Hovedforfatter:	Faisal, Shah
Andre forfattere:	Haque, Munima
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2024
Fag:	Cervical cancer Comparative analysis Predictive modeling Machine learning Healthcare infrastructure Cervix uteri > Cancer > Diagnosis. Machine learning > Computer programs
Online adgang:	http://hdl.handle.net/10361/22686

Lignende værker

Early detection of cervical cancer using deep neural networks
af: Akhund, Atoshi, et al.
Udgivet: (2023)

Decoding the functional roles of intronic microRNA miR-2355 and its host gene KLF7 in immunobiology of cervical cancer
af: Samia, Nure Sharaf Nower
Udgivet: (2021)

Machine learning as an indicator for breast cancer prediction
af: Shadman, Tahsin Mohammed, et al.
Udgivet: (2019)

Cervical Cancer Detection from Cervix Image Using Pap smear Imaging through CNN
af: Bhuiyan, Mazedul Haque, et al.
Udgivet: (2021)

Breast cancer prediction using different machine learning models
af: Khandker Al- Muhaimin, et al.
Udgivet: (2020)

Diagnosis of cervical cancer using effective hybrid model in Bangladesh
af: Saad-Ul-Kabir, Syed, et al.
Udgivet: (2021)

A comparative analysis of deep learning and hybrid models to diagnose multi-class skin cancer
af: Nawrin, Ishrat Nur, et al.
Udgivet: (2023)

Lung cancer detection and classification using machine learning
af: Arefin, Mahbubul, et al.
Udgivet: (2023)

A review on the socio-demographic and cultural factors associated with the delayed diagnosis of cervical cancer and possible interventions in screening attitude: From South Asian perspective
af: Tarannum, Nafisa, et al.
Udgivet: (2023)

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

Hypothesizing precise cancer treatments based on patient survival using machine learning & deep learning
af: Sakib, Hasibul, et al.
Udgivet: (2024)

Review on cervical cancer: effective vaccination project
af: Humayra, Ayonti
Udgivet: (2024)

Awareness of cervical cancer vaccination among educated females: a Bangladeshi perspective
af: Taniya, Sumaiya Akter
Udgivet: (2023)

Detection of acute Lymphocytic Leukemia (ALL) and its type by image processing and machine learning
af: Chowdhury, Himadri, et al.
Udgivet: (2019)

Survey on patients undergoing treatments for cervical, endometrial and ovarian cancer
af: Nawar, Anika
Udgivet: (2019)

Detection of skin cancer using Convolutional neural network
af: Ahsan, Abu Sa-adat Mohamed Moon-Im Al, et al.
Udgivet: (2020)

Predicting climate induced floods using machine learning
af: Saleh, Chowdhury Nafis, et al.
Udgivet: (2022)

Use of machine learning and weather predictions to bridge the gap between consumer demands and the market requirements of food crops
af: Hasan, Raad, et al.
Udgivet: (2021)

Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
af: Oishi, Fayza Rezwana, et al.
Udgivet: (2020)

Point-of care diagnostic devices in cancer detection
af: Yasmin, Rizwana
Udgivet: (2022)

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

Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
af: Islam, Zahedul, et al.
Udgivet: (2023)

An efficient deep learning approach to detect skin Cancer
af: Islam, Ashfaqul, et al.
Udgivet: (2022)

Developing a machine learning based prognostic model and a supporting web-based application for predicting the possibility of early diabetes and diabetic kidney disease
af: Amin, M.M. Shahriar, et al.
Udgivet: (2021)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
af: Toufique, S.M, et al.
Udgivet: (2024)

Recent advancement on breast cancer detection and treatment
af: Rahman, Sanjida
Udgivet: (2023)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
af: Alhossen, Md., et al.
Udgivet: (2021)

Skin cancer classification for seven types of skin lesions
af: Rahman, Md. Tawsifur, et al.
Udgivet: (2024)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
af: Sakir, Adnan, et al.
Udgivet: (2023)

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

Yield prediction for precision agriculture using extreme gradient boosting and support vector regression
af: Ahmed, Md. Sabbir, et al.
Udgivet: (2021)

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

A comparative study of lung cancer prediction using deep learning
af: Mugdho, Aka Mohammad, et al.
Udgivet: (2023)

Heart disease prediction using machine learning algorithms
af: Ali, Musfiq, et al.
Udgivet: (2019)

Statistics and informatics in molecular cancer research

Prostate cancer detection using deep learning neural network with transfer learning approach
af: Badhon, Ariful Islam Mahmud, et al.
Udgivet: (2022)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
af: Maliha, Miftahul Zannat, et al.
Udgivet: (2023)

Detecting Adverse Drug Reaction (ADR) with data mining and predicting its intensity with machine learning
af: Hussain, Nadib, et al.
Udgivet: (2018)

Prediction of anxiety and depression among the transgender in Bangladesh
af: Easha, Ishrat Jahan, et al.
Udgivet: (2023)

Investigation assistant with suspect anticipating intelligence
af: Abdullah, Saqueeb, et al.
Udgivet: (2019)