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.

Opis bibliograficzny
1. autor:	Faisal, Shah
Kolejni autorzy:	Haque, Munima
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2024
Hasła przedmiotowe:	Cervical cancer Comparative analysis Predictive modeling Machine learning Healthcare infrastructure Cervix uteri > Cancer > Diagnosis. Machine learning > Computer programs
Dostęp online:	http://hdl.handle.net/10361/22686

Podobne zapisy

Early detection of cervical cancer using deep neural networks
od: Akhund, Atoshi, i wsp.
Wydane: (2023)

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

Machine learning as an indicator for breast cancer prediction
od: Shadman, Tahsin Mohammed, i wsp.
Wydane: (2019)

Cervical Cancer Detection from Cervix Image Using Pap smear Imaging through CNN
od: Bhuiyan, Mazedul Haque, i wsp.
Wydane: (2021)

Breast cancer prediction using different machine learning models
od: Khandker Al- Muhaimin, i wsp.
Wydane: (2020)

Diagnosis of cervical cancer using effective hybrid model in Bangladesh
od: Saad-Ul-Kabir, Syed, i wsp.
Wydane: (2021)

A comparative analysis of deep learning and hybrid models to diagnose multi-class skin cancer
od: Nawrin, Ishrat Nur, i wsp.
Wydane: (2023)

Lung cancer detection and classification using machine learning
od: Arefin, Mahbubul, i wsp.
Wydane: (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
od: Tarannum, Nafisa, i wsp.
Wydane: (2023)

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

Hypothesizing precise cancer treatments based on patient survival using machine learning & deep learning
od: Sakib, Hasibul, i wsp.
Wydane: (2024)

Review on cervical cancer: effective vaccination project
od: Humayra, Ayonti
Wydane: (2024)

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

Detection of acute Lymphocytic Leukemia (ALL) and its type by image processing and machine learning
od: Chowdhury, Himadri, i wsp.
Wydane: (2019)

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

Detection of skin cancer using Convolutional neural network
od: Ahsan, Abu Sa-adat Mohamed Moon-Im Al, i wsp.
Wydane: (2020)

Predicting climate induced floods using machine learning
od: Saleh, Chowdhury Nafis, i wsp.
Wydane: (2022)

Use of machine learning and weather predictions to bridge the gap between consumer demands and the market requirements of food crops
od: Hasan, Raad, i wsp.
Wydane: (2021)

Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
od: Oishi, Fayza Rezwana, i wsp.
Wydane: (2020)

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

Machine learning In breast cancer prognosis and prediction
od: Chowdhury, Shah Abul Hasnat, i wsp.
Wydane: (2023)

Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
od: Islam, Zahedul, i wsp.
Wydane: (2023)

An efficient deep learning approach to detect skin Cancer
od: Islam, Ashfaqul, i wsp.
Wydane: (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
od: Amin, M.M. Shahriar, i wsp.
Wydane: (2021)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
od: Toufique, S.M, i wsp.
Wydane: (2024)

Recent advancement on breast cancer detection and treatment
od: Rahman, Sanjida
Wydane: (2023)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
od: Alhossen, Md., i wsp.
Wydane: (2021)

Skin cancer classification for seven types of skin lesions
od: Rahman, Md. Tawsifur, i wsp.
Wydane: (2024)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
od: Sakir, Adnan, i wsp.
Wydane: (2023)

A counseling system to predict the study path for freshmen
od: Usha, Rowshni Tasneem, i wsp.
Wydane: (2019)

Yield prediction for precision agriculture using extreme gradient boosting and support vector regression
od: Ahmed, Md. Sabbir, i wsp.
Wydane: (2021)

Machine learning for stress prediction
od: Salehin, Sherajus, i wsp.
Wydane: (2023)

A comparative study of lung cancer prediction using deep learning
od: Mugdho, Aka Mohammad, i wsp.
Wydane: (2023)

Heart disease prediction using machine learning algorithms
od: Ali, Musfiq, i wsp.
Wydane: (2019)

Statistics and informatics in molecular cancer research

Prostate cancer detection using deep learning neural network with transfer learning approach
od: Badhon, Ariful Islam Mahmud, i wsp.
Wydane: (2022)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
od: Maliha, Miftahul Zannat, i wsp.
Wydane: (2023)

Detecting Adverse Drug Reaction (ADR) with data mining and predicting its intensity with machine learning
od: Hussain, Nadib, i wsp.
Wydane: (2018)

Prediction of anxiety and depression among the transgender in Bangladesh
od: Easha, Ishrat Jahan, i wsp.
Wydane: (2023)

Investigation assistant with suspect anticipating intelligence
od: Abdullah, Saqueeb, i wsp.
Wydane: (2019)