International Business Machines Corporation

Shivangi Tak

Yash Veer Singh

Mandar Mutalikdesai

Kartikeya Vats

Ashish Rao

Anagha M

Sandipto Neogi

Pranjal Srivastava

Sridhar Jonnala

Saigeetha Aswathnarayanan Jegannathan

Shivam Ratnakar

Chinthalapudi Venkata Sai Vishnu Vardhan

V Datta Kamesam Jami

Naman Mathur

In an approach for automatically identifying one or more updates in a Scientific Drug Label (SL) relevant to a patient and incorporating the one or more updates into a Patient Drug Label (PL), a processor receives a pair of documents, wherein the pair of documents include the SL and the PL. A processor converts a complex medical language of the SL into a simplified patient friendly language. A processor identifies one or more words, one or more phrases, or one or more sentences that have been modified, inserted, or deleted. A processor searches for a location in the PL that closely maps to the one or more words, the one or more phrases, or the one or more sentences to the SL. A processor incorporates the one or more words, the one or more phrases, or the one or more sentences in a mapped location of the PL.

AI driven smart patient labeling system

An approach is provided in which the approach applies, by a first node, a first axiom to a set of data points to generate a set of first outputs. The approach applies, by a second node, a second axiom to the set of data points to generate a set of second outputs. The first node and the second node are part of a computer network that includes multiple nodes. The approach computes a first nuance based on a set of disagreements between the set of first outputs and the set of second outputs, and adjusts a reliability of the first node in the computer network based on the first nuance.

Preserving data integrity in cognitive multi-agent systems

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Gurgaon, India

Shivangi Tak