Apache cTAKES Pros and Cons

It helps creating Patient Health Profile from the Patient charts. Review collected by and hosted on G2.com.

It would havebeen better if it was a web based product, lack of APIs. Review collected by and hosted on G2.com.

A sophisticated and accessible tool for analysing clinical documents and reports. As it is written in Java, it is very reliable and scalable.

Easy to integrate as well. Review collected by and hosted on G2.com.

Data loads slowly at scale.

The UI needs to improve by a good margin to allow the users to sift through quickly.

Documentation can be improved significantly to allow a better experience. Review collected by and hosted on G2.com.

The cTakes tool is a free and very powerful tool to do an analysis of Clinical Documents and reports. It's highly robust and scalable as written is JAVA. Natural Language Processing helps in getting the Named Entity Recognition for the clinical entities which helps in creating NER models easily with this tool. Review collected by and hosted on G2.com.

Slow in loading high-resolution data, UI can be improved a bit, and also going through such vast documentation requires a lot of patience, and navigation. Search option in documentation will be really helpful Review collected by and hosted on G2.com.

Apache cTAKES is a potent tool to analyze and is powered by Natural language Processing. It helps to handle unstructured data and transform it into meaningful information for any business use case. It also has very well documentation and a community to help. Additionally highly scalable as written in java and works like a charm!! Review collected by and hosted on G2.com.

User interface and documentation covering basics with examples are only improvements area. It can also add support to handle multiple clouds source of inputs like AWS, GC, Azure, etc. Review collected by and hosted on G2.com.

Free of Cost

Easy-to-understand documentation

Scalable and can be used with Java which makes it Platform independent

Provides word tagging similar to NER in text-based machine learning Review collected by and hosted on G2.com.

Takes a lot of time when loading massive datasets

There is a scope for improvement in the UI/UX design of the tool

Could also implement themes in the tool as a good-to-have feature Review collected by and hosted on G2.com.

Its very easy to understand and even easy to implement. I see a great potential in this product. The documentation is insightful as compared to similar products. Review collected by and hosted on G2.com.

It's pretty great when it comes to implementation and products, but it seems it needs to be more versatile for various use cases to be more popular with developers. Review collected by and hosted on G2.com.

Apache cTakes is widely used to handle unstructured text data. It is open-source and highly scalable. One can easily integrate this with widely used programming languages like Java and Python. Installation is straightforward, and it can handle massive amounts of data. Review collected by and hosted on G2.com.

This product can only be used for unstructured text data. If the data is structured or in any other format, we can't use Apache cTakes. Also, integration is only available with some of the programming languages only. Review collected by and hosted on G2.com.

API in Java

Open-Source and Free

Good documentation and supportive community

Easy to Learn Review collected by and hosted on G2.com.

UI experience could have been better

Programming Language support could be more extended. Review collected by and hosted on G2.com.

The Natural Language Processing Approach is very nice with tokenization, element type and using pipelines. JCas is new to learn. Much Interested in exploring. Review collected by and hosted on G2.com.

Nothing as of now. But online ppt, animation videos for learning, live projects with complete code setup on required IDE and executing the project KT is required. Review collected by and hosted on G2.com.

Open source and free, parameterized pipeline building, fast and secure. Review collected by and hosted on G2.com.

Limited source system integration, cross-cloud integration can be enhanced to load data from multiple cloud sources. Review collected by and hosted on G2.com.