AI Solutions for Healthcare and Medical
Diagnosis and Disease Identification
The biggest challenge in medicine is correct diagnosis and identification of diseases, which makes it priority one in machine learning development. Healthcare data comes from myriad sources: hospitals, doctors, patients, caregivers, and research. The challenge is putting all the data together in a compatible format and using it to develop better healthcare networks and protocols. This is where machine learning comes in. The main purpose of machine learning applications specific to medicine and healthcare is to make data accessible and usable for improving prevention, diagnosis, and treatment as a matter of course.
There is much research going on regarding the use of machine learning and predictive analytics in customizing treatment to a person’s unique health history. If successful, this can result in optimized diagnosis and treatment protocols. Currently, the focus is on supervised learning where doctors can use genetic information and symptoms to narrow down diagnostic options or make an educated guess about a patient’s risk. This can lead to better preventive measures.
Electronic Health Records
The biggest obstacle to seamless electronic health records is the lack of synchronicity between the medical profession and the companies that develop electronic health record (EHR) systems. Healthcare AI developers need to understand the nature of healthcare data to provide automated EHR data management systems.
Xen.AI can help the Healthcare and Medical companies to apply artificial intelligence, machine learning, deep learning and data science technologies to improve the efficiency and reduce the operating cost.