Artificial Intelligence and big data are already being used in the healthcare sector. Cognitive computer systems, radiological diagnostics, surgical robots, and other robotic based systems are fields of application of big data and AI. Healthcare industry generates a large volume of digital and physical data waiting to be inferred upon. Applying AI and big data can yield beneficial information.
The rewards AI and big data bring in the healthcare industry are as follows.
1. Malware detection: Machine learning applications can effectively detect threats emerging against healthcare sectors today.
2. Automated healthcare diagnosis: The use of AI and big data enables monitoring complex patterns in identifying diseases forming a proper diagnosis.
3. Drug discovery: With big data solutions researchers engaged in improved drug discoveries. The speed of drug discovery can be enhanced with predictive learning.
4. Efficient responding to security breach: When comparing with conventional patterns the AI could more efficiently eradicate the threats after a security breach. AI is capable of continuous and automatic monitoring of network behavior so that threats within the network could be identified and rectified.
5. Improving patient outcomes: AI and big data can offer a more personalized treatment experience for patients. Patient treatment history can be made useful for this.
The disadvantages should also be considered:
1. Lack of privacy: The technology takes individual privacy for the greatest good. To get a comprehensive and effective look for patient big data must have access to everything including private information.
2. Data protection: A major concern with big data is secure and who has the authority to use the data.
3. Data ownership: Previously patient information was only on paper. With the advent of electronic health records, patient-generated information became available, ownership is less clear.
Even though there are potential risks with AI and big data it is growing in the healthcare industry.