Our Medical ML Library allows doctors and nurses to better diagnose their patients using a combination of Machine Learning and Natural Language Processing to cross-reference Electronic Health Records databases. Being a Machine learning software, diagnostic accuracy will increase as more data enters the Medical ML Library. This clinical tool will not only reduce the chances of misdiagnoses, but will prevent excessive treatment and unnecessary testing caused by misdiagnosis. In addition, doctors and nurses will have more time for a personal interaction with their patients yielding a faster and healthier recovery period, simultaneously improving the effectiveness and reliability of this tool in the health industry.
Placing inputs outside of the program scope will create an error due to lack of a large enough database. Patients who are unwilling to disclose their Personal Health Records would limit the volume of our Medical Library for a Machine Learning Software. We would need to guarantee the security and privacy of patient’s data against potential cyber attacks. Any breach or loss of sensitive information will affect the public and medical industry’s trust in the system.