Accelerated Diagnosis and Enhanced Patient Care Delivery with ACL Digital’s AI Platform
Overview
Develop a Healthcare Radiology Assistant System using Machine Learning models to extract insights by processing EHR/EMR and medical history. Development of AI Platform for Patient Diagnosis using Machine Learning models operating on EHR/EMR and other data sources.
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Challenges
Develop a Healthcare Radiology Assistant System by using ML models for extracting insights by processing EHR/EMR and medical history
Solution
- Deploy a team with experience in Data Engineering and Data Science
- Data Pre-processing using Hadoop, Spark, Kafka streaming for processing Image, Text, structured (SQL/NoSQL) and unstructured data (e.g. handwritten notes)
- Model exploration, Model development, Model training and validation for Image and text processing, anomaly detection, etc
- Generate actionable insights including:
- Alerts/Alarms
- OEE recommendations
- Actionable insights
- Disease segmentation
- Integration of solutions with Radiology Assistant and Physician Assist applications
Outcomes
- Developed a Healthcare Radiology Assistant System by using ML models for extracting insights by processing EHR/EMR and medical history
- It reduced time for diagnosis and provided much need information about patient to healthcare staff on fingertip
- Generated alerts base on diagnosis and OEE Recommendations
