Machine learning as an indicator for breast cancer prediction

Machine learning as an indicator for breast cancer prediction

Includes bibliographical references (pages 53-54).

Xehetasun bibliografikoak
Egile Nagusiak:	Shadman, Tahsin Mohammed, Akash, Fahim Shahriar, Ahmed, Mayaz
Beste egile batzuk:	Alam, Md.Ashraful
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	BRAC University 2019
Gaiak:	Breast cancer Cancer prediction Machine learning
Sarrera elektronikoa:	http://hdl.handle.net/10361/11431

Antzeko izenburuak

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

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

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

Breast cancer awareness seminars
nork: Anwer Khan Modern Medical College
Argitaratua: (2016)

Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study
nork: Faisal, Shah
Argitaratua: (2024)

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

Recent advancement on breast cancer detection and treatment
nork: Rahman, Sanjida
Argitaratua: (2023)

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

Natural products and their combinatory effects in breast cancer treatment
nork: Siddique, Md. Ayman
Argitaratua: (2021)

Targeted therapeutic options in the treatment of Breast Cancer
nork: Alam, Kazi Tasnuva
Argitaratua: (2022)

A review of Breast Cancer risk factor assessment on women in developing countries, cancer drug resistance, and Breast Cancer treatment in Bangladesh
nork: Raihan, Dilraj
Argitaratua: (2024)

The impact of breast cancer on women’s lives in Bangladesh
nork: Mobashera, Tayeeba Tum
Argitaratua: (2024)

Pooled analysis of progression-free survival and overall survival in phase II clinical trials of breast cancer
nork: Shobnam, Sohana
Argitaratua: (2024)

Drug repurposing: potential of Antimicrobial Drugs in Breast Cancer Treatment
nork: Chakraborty, Anuradha
Argitaratua: (2024)

A review on triple-negative breast cancer and its potential treatment
nork: Niasa, Jannatul Ferdous
Argitaratua: (2023)

Comparison of conventional doxorubicin with liposome encapsulated doxorubicin as a treatment of breast cancer-a review
nork: Akter, Honufa
Argitaratua: (2024)

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

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

Breast cancer therapy through Liposomal drug delivery system
nork: Ome, Nusrat Jahan
Argitaratua: (2024)

Targeting DHFR in breast cancer: exploring expression patterns and identifying potential inhibitors through docking studies
nork: Araf, Faiaz Fahim
Argitaratua: (2024)

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

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

Machine learning for stress prediction
nork: Salehin, Sherajus, et al.
Argitaratua: (2023)

Breast cancer in low-resource settings: Prioritizing the awareness and access programmes to overcome sociocultural and economic barriers for early detection and improved outcomes
nork: Iqbal, Mohammad Shamim, et al.
Argitaratua: (2017)

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

Pathway analysis of Disease-Gene associated network in the human breast cancer
nork: Lamia
Argitaratua: (2020)

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

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

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

A review on the potential of repurposing of metformin for colon cancer and breast cancer
nork: Oishy, Jannatun Noor
Argitaratua: (2024)

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

In silico analysis revealed hsa-miR-19a-3p and hsa-miR-19b-3p as two potential inhibitors of EGF mRNA in Breast Cancer
nork: Nuha, Nabiha Tahsin
Argitaratua: (2024)

Breast cancer in South Asia: a Bangladeshi perspective
nork: Hossain, Mohammad Sorowar, et al.
Argitaratua: (2017)

Predictive maintenance of HVAC system using supervised machine learning algorithms
nork: Fahim, Md. Zubayer Ahmed, et al.
Argitaratua: (2021)

Predicting depression in Bangladeshi undergraduates using machine learning
nork: Choudhury, Ahnaf Atef, et al.
Argitaratua: (2019)

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

Flight fare prediction using machine learning
nork: Noyon, Md. Shaim Hosan, et al.
Argitaratua: (2024)

Weather Pattern Extraction using Statistical Methods & Machine Learning Techniques
nork: Habib, Adria Binte
Argitaratua: (2021)

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

Emotion analysis using machine learning model and deep learning model on DEAP dataset
nork: Hasan, Anita, et al.
Argitaratua: (2022)