As we start this short second week; the switch team individuals start their research on their chosen projects.
First thing i started with to begging with my project is to understand the point of it as i read the literature review i have learned few cool things like there are several factors behind the reason of making Breast cancer significant public health problem in today’s society one of them is BC is one of the most common cancers among women, if Breast cancer found or diagnosed early it can improve the prognosis and the chance of the survival.
The classification of patients into malignant or benign groups is the subject of much research.
Early signs of breast cancer are:
- Lumps inside the breast or underarm area.
- Changes in breast size and shapes.
- Pain in a specific area that doesn’t go away.
- Swelling and redness.
The reason why we want computers to classify cancer for us is to identify features (Pathologists can’t identify from the pictures alone).
The first day working on the project I downloaded Anaconda IDE supporting Jupyter as a virtual programming environment.
I have downloaded the UCI Machine Learning Repository for breast cancer dataset from the tutorial.The program uses a curve-fitting algorithm, to compute ten features from each one of the cells in the sample, than it calculates the mean value, extreme value and standard error of each feature for the image, returning a 30 real-valuated vector.
The first phase is data exploration where I imported the necessary libraries to examine the dataset using the pandas’ head() method. Part of this phase is to find the dimensions of the dataset using the panda dataset shape attribute. In the Diagnosis column the prediction for the cancer type is M=malignant or B=benign 1 means malignant and 0 means benign.
Machine learning plays an important role in the health field. On the second day Dr. Souptik Barua from Rice University is postdoctoral research scientist and his background is in data science machine learning competition analysis; also we had some young scholars join us during the presentation. During this presentation he discussed how more and more apps are starting to appear on those technologies.
Diabetes status in America 2020 the reports are about one in every ten people and we can use technology to manage and prevent diabetes such as smart watches and one out of five didnt know they have diabetes. Why is diabetes such a big concern is because long term diabetes leads to complications of the heart, or could lead to amputations of the feet or cardiovascular incidents such as stroke.
On the third day Dr. Jesica Ramella from FIU talked about diabetes and Cardiovascular and discussed the grand challenge of finding a way to manage diabetes and diabetes and cardiovascular disease in a population that doesn’t have standard access to health care it led to underserved population across the United States and of course they had to do that because it’s the biggest problem that we face right now.
It’s where every 30 seconds one American will be diagnosed with diabetes and another will suffer a coronary. Cardiovascular disease is the number one cause of death globally, not just in the United States. Statistics are really dramatic where one in four people have cardiovascular disease. So many organizations are looking at managing cardiovascular disease for the survivors. Diabetes by itself in the US is the 7th leading cause of death.
Let’s connect obesity and cardiovascular disease where the Hispanic and black adults population get affected the most and they are also likely to have heart failure and coronary heart disease.
40 million people in the United states have smartwatches.The market in the next few weeks will explode with wearable devices.
These devices easily can read your heart rate and measure your pulse, sometimes the accuracy of reading the heart rate is right. Smartwatches don’t work with all people in particular with different races with different skin tones and so many articles come up with that all the fitness trackers are racist.
Looking at the principle of the technique and what is theoretically the error even is when doing a standard type of activity like walking and sitting based on instrument design. PPG or photoplethysmography and blood pressure.
Using the PPG sensor it will look at the mechanical property of the artery using something called the final element to create a realistic dilation of an artery on this specific diameter and specific mechanical property. Those mechanical properties make predictions about the dilation of the art itself.
