The importance of data quality in the success of artificial intelligence and natural language processing in the field of health

In the world of health technology, data quality is of great importance. In a special webinar, experts in this field discussed the high importance of data standards, accurate coding of medical concepts and synonymy in improving solutions based on artificial intelligence and natural language processing in the health field. This meeting was dedicated to examining the impact of these issues on improving patient outcomes, creating innovation in health technology, and improving the efficiency of artificial intelligence systems.

The impact of data quality on the success of artificial intelligence and NLP in health

Quality data is the basis of systems efficiency Nice processingN natural And language models are great in health. Since AI models operate on their input data, if the input data is not accurate, the output will not be as reliable. In this webinar, prominent experts from reputable companies emphasized the need to increase data quality to achieve more accurate solutions.

Data quality challenges in medical care

Participants in this session pointed out various problems that exist in the way of improving data quality, including the complexity of unstructured medical data. In the examples presented by each of the speakers, the obstacles in the quality of clinical data and the challenges in training artificial intelligence models were discussed. As an example, IQVIA’s Dr. Calum Yacobian pointed out the complexity of extracting key data from medical notes and emphasized that the use of artificial intelligence in this direction has helped reduce time and increase accuracy.

The importance of governance systems in data management

Ivana Naimirod, Chief Operating Officer of IMO Health, pointed out the importance of implementing governance systems to monitor data quality and ensure the security of sensitive patient data. According to him, if organizations do not have strict monitoring processes and specific standards in the use of artificial intelligence data, the possibility of problems related to privacy and data security will increase.

Using artificial intelligence to improve data

Experts pointed out that the use of artificial intelligence as a tool to clean and improve the quality of data has provided a new possibility in this field. Gigi Yuan of Cohere Health explained how her team uses big language models to identify and correct erroneous data. This process allows professionals to identify and correct poor quality data more quickly and accurately.

The future of artificial intelligence in the field of health

At the end of the session, each of the participants noted the exciting opportunities that artificial intelligence provides for improving the quality of medical care. They believe that in the future, artificial intelligence can bring better results to patients and improve decision-making processes with the help of more accurate tools that are familiar with clinical language and content.

This webinar showed that data quality plays a key role in the success of AI technologies in health and that cooperation between technical teams and medical staff is necessary to achieve sustainable solutions.