Early Breast Cancer Detection Device

Breast cancer is one of most widespread life-threatening cancers in the world. The prevailing procedures to detect breast cancer include mammogram, ultrasound, biopsy tests and MRI and its spectroscopy. This is costly and time-consuming which means more effective solutions were still needed. Therefo

Project Title

Early Breast Cancer Detection Device

Project Area of Specialization

Artificial Intelligence

Project Summary

Breast cancer is one of most widespread life-threatening cancers in the world. The prevailing procedures to detect breast cancer include mammogram, ultrasound, biopsy tests and MRI and its spectroscopy. This is costly and time-consuming which means more effective solutions were still needed. Therefore, keeping the need and importance in view, we have used Rough-Fuzzy hybrid technique to produce an early breast cancer detection model to contribute in this area. For a computer scientist, given the fact that most researches are clinical and biological in nature, early detection of breast cancer capitalizing on data mining has remained a difficult task. In order to develop the model, this study used Wisconsin Breast Cancer Dataset which was based on ten attributes. As per the study results, there are 22 independent descriptions (of attributes) which strongly support malignant (infectious) stage of cancer. Similarly, 19 descriptions are recorded for benign stage and 10 descriptions supported both stages (i.e., malignant and benign).

Project Objectives

World Health Organization says that 1/3 lives can be saved if breast cancer is detected in its early stages.

Based on our findings, once the product is ready then through this we would be able to save a lot innocent lives. This is going to be a bra insert wearable which even a laywoman can use it. All they have to is to wear the device and just click the icon of the application software. Then Our device takes data and transfers to the application software with wifi module which analyzes the data with the help of our Artificial Intelligence-based algorithm which is inbuilt in our app. We have successfully achieved 96.59% accuracy which is very clearly discussed in our impact factor paper titled as "A Rough Fuzzy Model for Early Breast Cancer Detection". Making available to the unavailable and affordable to the unaffordable in Pakistan is the prime objective and need of our country. If all went as per the plan then our objective of affecting 40 million out 100 million women of Pakistan would be met in the next five years. 

Project Implementation Method

Project Implementation begins with the following major milestones. We have achieved some of them already and remaining would be achieved in coming 3 months.

We are done with literature review about the existing techniques to find breast cancer in its early stages (stage 1 and stage 2). We have our world-renowned dataset for breast cancer. We have finalized algorithms (a hybrid one) and got 96.59% accuracy and came with the results which would make our device capable enough to detect breast cancer with only 2 to 3 descriptors which we dually justified with concrete findings in our paper. These are parts or rather milestones which we have already achieved.

However, we are looking forward to make application software, hardware working prototype with 6 sensors in this coming three months.

Benefits of the Project

The major benefits of this project are the availability of self-examination device where women with have to buy this device from there consultant, with whom we would have our business to business relation. Second most important benefit of it, is the chances of saving 1/3 lives with early breast cancer detection device. Third benefit of it is being affordable, the estimated cost of this device is between 6,000 to 7,000 that means it would be quite affordable every individual. 

Technical Details of Final Deliverable

Final deliverable is going to be the combination of both application software and hardware (early breast cancer detection device). 

Our hardware would have at least 4 sensors: humidity sensors, temperature sensor, ultrasonic sensor (to monitor if the women has worn or not), Wi-Fi module (to transfer data from device to application software), furthermore raspberry pi would be used initially as microprocessor. 

After that, our application software would analyze the case against rules which are mentioned in Appendix A section of the paper. Then application software would generate alarm in case of finding any abnormality. 

After that, our application software would analyze the case against rules which are mentioned in Appendix A section of the paper. Then application software would generate alarm in case of finding any abnormality. 

Final Deliverable of the Project

Hardware System

Type of Industry

IT , Medical , Health

Technologies

Artificial Intelligence(AI), Internet of Things (IoT), Wearables and Implantables

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com