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.
| Главный автор: | |
|---|---|
| Другие авторы: | |
| Формат: | Диссертация |
| Язык: | English |
| Опубликовано: |
Brac University
2024
|
| Предметы: | |
| Online-ссылка: | http://hdl.handle.net/10361/22686 |
| id |
10361-22686 |
|---|---|
| record_format |
dspace |
| spelling |
10361-226862024-04-30T04:58:39Z Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study Faisal, Shah Haque, Munima Department of Mathematics and Natural Sciences, Brac University Cervical cancer Comparative analysis Predictive modeling Machine learning Healthcare infrastructure Cervix uteri--Cancer--Diagnosis. Machine learning--Computer programs 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. Cataloged from PDF version of thesis. Includes bibliographical references (pages 61-66). This proposal presents a comprehensive investigation of cervical cancer frequency and patterns, with a focus on a multi-national perspective, particularly highlighting the circumstance in Bangladesh. Utilizing a mix of auxiliary information survey, comparative investigation, and predictive modeling, this study sheds light on the worldwide landscape of cervical cancer, emphasizing disparities in rate, screening hones, and healthcare framework. The inquire about utilizes machine learning calculations, especially linear regression, to extend future patterns of cervical cancer in Bangladesh up to 2050. Moreover, an in-depth examination of statistic, clinical, and treatment characteristics of 223 cervical cancer patients in Bangladesh offers basic bits of knowledge into components affecting results. Key discoveries uncover noteworthy fluctuations in treatment and discovery techniques over nations, underscoring the requirement for more harmonized worldwide healthcare approaches. The predictive analysis indicates a potential stabilization in cervical cancer cases in Bangladesh, suggesting a positive trend due to ongoing healthcare efforts. This proposition contributes to the existing body of information on cervical cancer, giving profitable bits of knowledge for healthcare arrangement definition and execution, especially in resource-limited settings. Shah Faisal B. Biotechnology 2024-04-28T08:11:45Z 2024-04-28T08:11:45Z ©2023 2023-12 Thesis ID 20236022 http://hdl.handle.net/10361/22686 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 66 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Cervical cancer Comparative analysis Predictive modeling Machine learning Healthcare infrastructure Cervix uteri--Cancer--Diagnosis. Machine learning--Computer programs |
| spellingShingle |
Cervical cancer Comparative analysis Predictive modeling Machine learning Healthcare infrastructure Cervix uteri--Cancer--Diagnosis. Machine learning--Computer programs Faisal, Shah Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study |
| description |
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. |
| author2 |
Haque, Munima |
| author_facet |
Haque, Munima Faisal, Shah |
| format |
Thesis |
| author |
Faisal, Shah |
| author_sort |
Faisal, Shah |
| title |
Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study |
| title_short |
Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study |
| title_full |
Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study |
| title_fullStr |
Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study |
| title_full_unstemmed |
Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study |
| title_sort |
comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/22686 |
| work_keys_str_mv |
AT faisalshah comparativeanalysisandmachinelearningpredictionsofcervicalcancerincidenceamultinationalstudy |
| _version_ |
1814308914980716544 |