Pinned Repositories
dsaa-fdw_afg_population-FEWSNET
breast_cancer_classification
# Breast Cancer Classification Breast cancer is a common cancer in women, and one of the major causes of death among women around the world. Invasive ductal carcinoma (IDC) is the most widespread type of breast cancer with about 80% of all diagnosed cases. IDC is cancer that began growing in a milk duct and has invaded the fibrous or fatty tissue of the breast outside of the duct. Early accurate diagnosis plays an important role in choosing the right treatment plan and improving survival rate among the patients. In recent years, efforts have been made to predict and detect all types of cancers by employing artificial intelligence. An appropriate dataset is the first essential step to achieve such a goal. This paper introduces a histopathological microscopy image dataset of 922 images related to 124 patients with IDC. The dataset has been published and is accessible through the web at: http://databiox.com. The distinctive feature of this dataset as compared to similar ones is that it contains an equal number of specimens from each of three grades of IDC, which leads to approximately 50 specimens for each grade. ![](https://upload.wikimedia.org/wikipedia/commons/thumb/4/47/Lobules_and_ducts_of_the_breast.jpg/504px-Lobules_and_ducts_of_the_breast.jpg) ## Introduction In Kenya, cancer is the third leading cause of death after infectious and cardiovascular diseases. From 2012 to 2018, the annual incidence of cancer increased from 37,000 to 47,887 new cases.7 During the same period, annual cancer mortality rose almost 16%, from 28,500 to 32,987 cancer-related deaths. The number of new cancer cases is expected to rise by more than 120% over the next 2 decades.
climate_indices
Climate indices for drought monitoring, community reference implementations in Python
geopy
Geocoding library for Python.
Kaggle_Competition
life_insurance_analysis
photo
RHEAS
Regional Hydrologic Extremes Assessment System
Sen1Floods11
yield-estimation
samburu's Repositories
samburu/breast_cancer_classification
# Breast Cancer Classification Breast cancer is a common cancer in women, and one of the major causes of death among women around the world. Invasive ductal carcinoma (IDC) is the most widespread type of breast cancer with about 80% of all diagnosed cases. IDC is cancer that began growing in a milk duct and has invaded the fibrous or fatty tissue of the breast outside of the duct. Early accurate diagnosis plays an important role in choosing the right treatment plan and improving survival rate among the patients. In recent years, efforts have been made to predict and detect all types of cancers by employing artificial intelligence. An appropriate dataset is the first essential step to achieve such a goal. This paper introduces a histopathological microscopy image dataset of 922 images related to 124 patients with IDC. The dataset has been published and is accessible through the web at: http://databiox.com. The distinctive feature of this dataset as compared to similar ones is that it contains an equal number of specimens from each of three grades of IDC, which leads to approximately 50 specimens for each grade. ![](https://upload.wikimedia.org/wikipedia/commons/thumb/4/47/Lobules_and_ducts_of_the_breast.jpg/504px-Lobules_and_ducts_of_the_breast.jpg) ## Introduction In Kenya, cancer is the third leading cause of death after infectious and cardiovascular diseases. From 2012 to 2018, the annual incidence of cancer increased from 37,000 to 47,887 new cases.7 During the same period, annual cancer mortality rose almost 16%, from 28,500 to 32,987 cancer-related deaths. The number of new cancer cases is expected to rise by more than 120% over the next 2 decades.
samburu/climate_indices
Climate indices for drought monitoring, community reference implementations in Python
samburu/geopy
Geocoding library for Python.
samburu/Kaggle_Competition
samburu/life_insurance_analysis
samburu/photo
samburu/RHEAS
Regional Hydrologic Extremes Assessment System
samburu/Sen1Floods11
samburu/yield-estimation