At Insife we are 100% dedicated to deliver on the ever-growing demand for complete compliance and the need for solutions that minimize the operational footprint with seamless integration, automation, and the overall reduction of manual processing. Therefore, we have upgraded HALOPV 4.0 with JOHN SNOW LABS, the most comprehensive ML/AI for NLP (Natural Language Processing)
The world is changing at a staggering pace, and two significant developments in customer behaviour and regulatory trends have accelerated changes within the field of Pharmacovigilance.
Beast, Beauty or Both?
Market first: Drastic changes in customer-behaviour.
Unlike ever before customers are focused on observing and reporting adverse effects from health care products. Maybe – and probably – as a consequence of the global Covid vaccination-program and the debate following it. What we see is that the heightened attention to adverse effects of the different vaccines also spread to other types of medication and health care products.
The other change is that patient and drug safety have gained a higher priority on the political agenda. With the increasing globalization of the Life Science industry and cross-border trading and corporation, lawmakers aim to further enforce patient safety and implement regulation to support trust, transparency, and reliability.
The good news is that the changes in customer-behaviour and increase in reporting means that the Life Science-industry will be better able to understand the safety profile of their products having access to more adverse event reports. The challenge is that this potentially means a heavier workload. Unless they embrace the latest technology available, and it is in this light, and to continuously provide our users with the best digital support to handle both current and future market and regulatory demands, we have launched HALOPV 4.0 with the inclusion of JOHN SNOW LABS: The market leading ML/AI for NLP.
About JOHN SNOW LABS
With a market share of approximately 33% SPARK NLP ML/AI is the most widely used NLP library in the world. With features such as word segmentation, sentence detector (DL models), coreference resolution, unsupervised keywords extraction, language detection & identification (up to 375 languages), multi-class text classification, multi-label text classification, named entity recognition and much, much more.
SPARK NLP has 10,000+ pre-trained models in 200+ languages. It can run any cloud and is natively scalable to large clusters.
SPARK NLP is cloud and therefore delivers flexibility and scalability.
What this means is that
Spark NLP ML/AI is the market’s most accurate in terms of solving classification problems
Spark NLP ML/AI plays a big role in name entity recognition, multi-class classification, de-identification of important entity and resolution of different entities to their different codes and much more
It is much faster to train in comparison to others (around 1.8x or 2x times)
The time to parse cases through the models is reduced by 50%
It delivers easiness and speed to query large data volumes through SQL
It can scale-up and out to accommodate increasing volumes of data
To know more about JOHN SNOW LABS' SPARK NLP & Healthcare NLP Go to John Snow Labs
Met Insife ML/AI expert Amit Arora Amit Arora | insife
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