Hypothesizing precise cancer treatments based on patient survival using machine learning & deep learning

Hypothesizing precise cancer treatments based on patient survival using machine learning & deep learning

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

Xehetasun bibliografikoak
Egile Nagusiak:	Sakib, Hasibul, Alok, Aditto Baidya, Huq, Fardin, Ullah, Shamsil Arafin, Ghosh, Riya
Beste egile batzuk:	Shakil, Arif
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	SEER Data Machine learning Deep Learning Cancer Survivability Machine learning. Data mining. Cancer > Chemotherapy. Cancer > Radiotherapy.
Sarrera elektronikoa:	http://hdl.handle.net/10361/22713

Antzeko izenburuak

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

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

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

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

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

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

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

Comparing effectiveness and safety of combination therapy for esophageal and gastro esophageal junction cancer: a comprehensive meta-analysis
nork: Abir, Shifaty Nur
Argitaratua: (2024)

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

Cancer classification using deep learning from medical image data
nork: Monir, Raiyan Janik, et al.
Argitaratua: (2022)

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

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

Clinical outcomes and safety comparison of gemcitabine plus cisplatin, capecitabine monotherapy, and gemcitabine plus oxaliplatin in the management of gallbladder carcinoma: a comprehensive meta-analysis
nork: Rahman, Sanjida
Argitaratua: (2024)

Detection of fake identities on twitter using supervised machine learning
nork: Rahman, MD. Takiur, et al.
Argitaratua: (2019)

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)

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

Multimodal human detection in disaster situations using deep learning & artificial intelligence
nork: Rafat, Md. Tasbi, et al.
Argitaratua: (2023)

Statistics and informatics in molecular cancer research

A decentralized learning-based approach to classify colorectal cancer using Deep Learning Leveraging XAI
nork: Mubin, Kazi Ehsanul, et al.
Argitaratua: (2022)

An implementation and analysis of deep learning models for the detection of wheat diseases
nork: Zubair, Ahmad, et al.
Argitaratua: (2024)

A Study of gainful employment of learners receiving skills training in the informal sector using Machine Learning
nork: Raizan, Syed Ahsan, et al.
Argitaratua: (2021)

An examination of therapeutic synergy: a comprehensive meta-analysis comparing the efficacy of TAS-102 and FOLFOX as a combination therapy for colon cancer
nork: Hasan, Amit
Argitaratua: (2024)

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

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
nork: Ifty, Md. Hasin Sarwar, et al.
Argitaratua: (2024)

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

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

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

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

Machine learning and statistics : the interface /
Argitaratua: (1997)

Cancer risk factors: a critical review
nork: Tabassum, Tahsina
Argitaratua: (2017)

An efficient deep learning approach to classify white blood cells
nork: Turja, Afif Ibna Kadir Khan, et al.
Argitaratua: (2024)

Effect of performance status on efficacy endpoints in phase II trials of non-small cell lung cancer
nork: Paul, Pulock
Argitaratua: (2024)

Public vehicle ETA system using machine learning
nork: Kabir, Md. Miraz, et al.
Argitaratua: (2018)

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

Document template identification and data extraction using machine learning and deep learning approach
nork: Roy, Kaushik, et al.
Argitaratua: (2024)

Flood prediction using ensemble machine learning models
nork: Rahman, Tanvir
Argitaratua: (2024)

Alumni opportunities using machine learning
nork: Siaum, Arshif Sharlimin, et al.
Argitaratua: (2019)

Analysis of the impact of online education using EEG signals and machine learning algorithms
nork: Hoque, Ehsanul, et al.
Argitaratua: (2021)

Start up business solution using machine learning
nork: Sohan, Saad Ahmed, et al.
Argitaratua: (2018)

Impact of machine learning and deep learning on biomedical applications and healthcare industry
nork: Kabir, Md Saif, et al.
Argitaratua: (2024)