AI Solutions for Healthcare and Medical

Diagnosis and Disease Identification
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.
Personalized Medicine
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.
Personalized Medicine
Electronic Health Records
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.
Medical Imaging
One of the most promising areas of health innovation is the application of artificial intelligence (AI), primarily in medical imaging. We can use AI, Machine Learning and Deep Learning technologies to help the medical professionals to analysis the X-Rays and MRI images.
Medical Imaging


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.

Customer Case Studies

Machine Learning based solution for Medical and Business transcription

 

Challenges: 

Medical transcription company with operations in USA and India is currently using hundreds of transcription agents to listen to the medical and business audio notes and manually convert those to text. Company is finding it very difficult to attract and retain human agents to scale the team within the tight operating costs and the thin margin. Company is loosing business opportunites due to lack of transcription agents.

 

 

Solution:

Xen.AI is developing a machine learning and natural language based transcription engine that can automatically process the audio input and produce equivalent text outputs. This solution will help the company to save the time and resources used to do the transcription works.

 

We can help build innovative solutions and applications using Artificial Intelligence technologies.